artificial intelligence


Summary: The study and implementation of techniques and methods for designing computer systems to perform functions normally associated with human intelligence, such as understanding language, learning, reasoning, problem solving, etc.

Top Publications

  1. ncbi A review of feature selection techniques in bioinformatics
    Yvan Saeys
    Department of Plant Systems Biology, VIB, B 9052 Ghent, Belgium
    Bioinformatics 23:2507-17. 2007
  2. ncbi Protein homology detection by HMM-HMM comparison
    Johannes Söding
    Department of Protein Evolution, Max Planck Institute for Developmental Biology Spemannstrasse 35, D 72076 Tubingen, Germany
    Bioinformatics 21:951-60. 2005
  3. ncbi A global geometric framework for nonlinear dimensionality reduction
    J B Tenenbaum
    Department of Psychology, Stanford University, Stanford, CA 94305, USA
    Science 290:2319-23. 2000
  4. ncbi Nonlinear dimensionality reduction by locally linear embedding
    S T Roweis
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, UK
    Science 290:2323-6. 2000
  5. ncbi Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
    Kuo Chen Chou
    Gordon Life Science Institute, San Diego, CA 92130, USA
    Bioinformatics 21:10-9. 2005
  6. pmc Predicting linear B-cell epitopes using string kernels
    Yasser El-Manzalawy
    Artificial Intelligence Laboratory, Iowa State University, Ames, IA 50010, USA
    J Mol Recognit 21:243-55. 2008
  7. ncbi Reverse engineering of regulatory networks in human B cells
    Katia Basso
    Institute for Cancer Genetics, 1300 St Nicholas Avenue, Room 912, New York, New York 10032, USA
    Nat Genet 37:382-90. 2005
  8. ncbi Gene prediction with a hidden Markov model and a new intron submodel
    Mario Stanke
    Institut fur Mikrobiologie und Genetik, Abteilung Bioinformatik, Universitat Gottingen, Gottingen, Germany
    Bioinformatics 19:ii215-25. 2003
  9. ncbi Machine learning in bioinformatics
    Pedro Larrañaga
    Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel de Lardizabal, 1, 20018 San Sebastian, Spain
    Brief Bioinform 7:86-112. 2006
  10. pmc Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences
    Yanzhi Guo
    College of Chemistry, Sichuan University, Chengdu 610064 and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610041, P R China
    Nucleic Acids Res 36:3025-30. 2008

Detail Information

Publications317 found, 100 shown here

  1. ncbi A review of feature selection techniques in bioinformatics
    Yvan Saeys
    Department of Plant Systems Biology, VIB, B 9052 Ghent, Belgium
    Bioinformatics 23:2507-17. 2007
  2. ncbi Protein homology detection by HMM-HMM comparison
    Johannes Söding
    Department of Protein Evolution, Max Planck Institute for Developmental Biology Spemannstrasse 35, D 72076 Tubingen, Germany
    Bioinformatics 21:951-60. 2005
    ..Protein homology detection and sequence alignment are at the basis of protein structure prediction, function prediction and evolution...
  3. ncbi A global geometric framework for nonlinear dimensionality reduction
    J B Tenenbaum
    Department of Psychology, Stanford University, Stanford, CA 94305, USA
    Science 290:2319-23. 2000
  4. ncbi Nonlinear dimensionality reduction by locally linear embedding
    S T Roweis
    Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, UK
    Science 290:2323-6. 2000
    ..By exploiting the local symmetries of linear reconstructions, LLE is able to learn the global structure of nonlinear manifolds, such as those generated by images of faces or documents of text...
  5. ncbi Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
    Kuo Chen Chou
    Gordon Life Science Institute, San Diego, CA 92130, USA
    Bioinformatics 21:10-9. 2005
    ..Although the results were quite encouraging, the entire prediction process was based on the amino acid composition alone without including any sequence-order information. Therefore, it is worthy of further investigation...
  6. pmc Predicting linear B-cell epitopes using string kernels
    Yasser El-Manzalawy
    Artificial Intelligence Laboratory, Iowa State University, Ames, IA 50010, USA
    J Mol Recognit 21:243-55. 2008
    ..Our homology-reduced data set and implementations of BCPred as well as the APP method are publicly available through our web-based server, BCPREDS, at:
  7. ncbi Reverse engineering of regulatory networks in human B cells
    Katia Basso
    Institute for Cancer Genetics, 1300 St Nicholas Avenue, Room 912, New York, New York 10032, USA
    Nat Genet 37:382-90. 2005
    ..The newly identified MYC targets include some major hubs. This approach can be generally useful for the analysis of normal and pathologic networks in mammalian cells...
  8. ncbi Gene prediction with a hidden Markov model and a new intron submodel
    Mario Stanke
    Institut fur Mikrobiologie und Genetik, Abteilung Bioinformatik, Universitat Gottingen, Gottingen, Germany
    Bioinformatics 19:ii215-25. 2003
    ..Gene finding programs have achieved relatively high accuracy on short genomic sequences but do not perform well on longer sequences with an unknown number of genes in them. Here existing programs tend to predict many false exons...
  9. ncbi Machine learning in bioinformatics
    Pedro Larrañaga
    Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel de Lardizabal, 1, 20018 San Sebastian, Spain
    Brief Bioinform 7:86-112. 2006
    ..Applications in genomics, proteomics, systems biology, evolution and text mining are also shown...
  10. pmc Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences
    Yanzhi Guo
    College of Chemistry, Sichuan University, Chengdu 610064 and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610041, P R China
    Nucleic Acids Res 36:3025-30. 2008
    ..The prediction software and all data sets used in this article are freely available at
  11. ncbi AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis
    Klaus Kayser
    UICC TPCC, Institute of Pathology, Charite, Berlin, Germany
    Folia Histochem Cytobiol 47:355-61. 2009
    ..By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1...
  12. pmc I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure
    Emidio Capriotti
    Laboratory of Biocomputing, CIRB Department of Biology, University of Bologna via Irnerio 42, 40126 Bologna, Italy
    Nucleic Acids Res 33:W306-10. 2005
    ..0 as a unique and valuable helper for protein design, even when the protein structure is not yet known with atomic resolution. Availability:
  13. pmc From disease association to risk assessment: an optimistic view from genome-wide association studies on type 1 diabetes
    Zhi Wei
    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, United States of America
    PLoS Genet 5:e1000678. 2009
    ..We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays...
  14. pmc Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010
    Berry de Bruijn
    Institute for Information Technology, National Research Council, Ottawa, Ontario, Canada
    J Am Med Inform Assoc 18:557-62. 2011
    ..In this paper, the authors describe the design and performance of three state-of-the-art text-mining applications from the National Research Council of Canada on evaluations within the 2010 i2b2 challenge...
  15. ncbi Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
    Xi Bin Zhou
    School of Chemistry and Chemical Engineering, Sun Yat Sen University, Guangzhou 510275, People s Republic of China
    J Theor Biol 248:546-51. 2007
    ..J. Proteome Res. 2, 183-190]. The overall accuracy thus obtained was 80.87%. The significant enhancement in the accuracy indicates that the current method might play a complementary role to the exiting methods...
  16. ncbi Predicting protein-protein interactions from sequence using correlation coefficient and high-quality interaction dataset
    Ming guang Shi
    Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, 230031 Hefei, China
    Amino Acids 38:891-9. 2010
    ..94% using gold standard positives and gold standard negatives datasets. The source code of MATLAB and the datasets are available on request under
  17. ncbi Prediction-based fingerprints of protein-protein interactions
    Aleksey Porollo
    Division of Biomedical Informatics, Children s Hospital Research Foundation, Cincinnati, Ohio 45229, USA
    Proteins 66:630-45. 2007
    ..42, as opposed to up to 70% classification accuracy and up to 0.3 Matthews correlation coefficient for methods that do not utilize RSA prediction-based fingerprints. The new method is available at
  18. ncbi A (sub)graph isomorphism algorithm for matching large graphs
    Luigi P Cordella
    Dipartimento di Informatica e Sistemistica, Universitá di Napoli Federico II Via Claudio 21, I 80125 Napoli, Italy
    IEEE Trans Pattern Anal Mach Intell 26:1367-72. 2004
  19. ncbi Morphological classification of brains via high-dimensional shape transformations and machine learning methods
    Zhiqiang Lao
    Section for Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
    Neuroimage 21:46-57. 2004
  20. pmc Machine learning and its applications to biology
    Adi L Tarca
    PLoS Comput Biol 3:e116. 2007
  21. ncbi Support vector machines for temporal classification of block design fMRI data
    Stephen LaConte
    Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, 30322, USA
    Neuroimage 26:317-29. 2005
    ..For both CVA and SVM, we have classified individual time samples of whole brain data, with TRs of roughly 4 s, thirty slices, and nearly 30,000 brain voxels, with no averaging of scans or prior feature selection...
  22. pmc Prediction of RNA binding sites in proteins from amino acid sequence
    Michael Terribilini
    Bioinformatics and Computationa Biology, Graduate Program, Iowa State University, Ames, Iowa 50010, USA
    RNA 12:1450-62. 2006
    ..RNABindR is available as a Web tool from
  23. ncbi MIReNA: finding microRNAs with high accuracy and no learning at genome scale and from deep sequencing data
    Anthony Mathelier
    UPMC Universite Paris 06, FRE3214, Génomique Analytique, Paris, France
    Bioinformatics 26:2226-34. 2010
    ..Several computational methods were developed to detect new miRNAs starting from known ones or from deep sequencing data, and to validate their pre-miRNAs...
  24. ncbi TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples
    Sanghamitra Bandyopadhyay
    Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India
    Bioinformatics 25:2625-31. 2009
    ..Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training...
  25. pmc COBEpro: a novel system for predicting continuous B-cell epitopes
    Michael J Sweredoski
    Department of Computer Science, University of California, Irvine, 92697 3435, USA
    Protein Eng Des Sel 22:113-20. 2009
    ..829 on the fragment epitopic propensity scoring task and an AUC up to 0.628 on the residue epitopic propensity scoring task. COBEpro is incorporated into the SCRATCH prediction suite at
  26. pmc Musite, a tool for global prediction of general and kinase-specific phosphorylation sites
    Jianjiong Gao
    Department of Computer Science, University of Missouri, Columbia, Missouri 65211, USA
    Mol Cell Proteomics 9:2586-600. 2010
    ..Musite is available at
  27. pmc Machine learning methods for metabolic pathway prediction
    Joseph M Dale
    Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA
    BMC Bioinformatics 11:15. 2010
    ..One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism...
  28. ncbi Bayesian ranking of biochemical system models
    Vladislav Vyshemirsky
    Department of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK
    Bioinformatics 24:833-9. 2008
    ..There are a number of methods available to compute the marginal likelihood approximately. A detailed investigation of such methods is required to find ones that perform appropriately for biochemical modelling...
  29. pmc Recommending MeSH terms for annotating biomedical articles
    Minlie Huang
    State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, PR China
    J Am Med Inform Assoc 18:660-7. 2011
    ..Here, we report a novel approach to facilitate MeSH indexing, a challenging task of assigning MeSH terms to MEDLINE citations for their archiving and retrieval...
  30. pmc nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms
    Lei Bao
    Department of Molecular Sciences, Center of Genomics and Bioinformatics, University of Tennessee Health Science Center, 858 Madison Avenue, Memphis, TN 38163, USA
    Nucleic Acids Res 33:W480-2. 2005
    ..nsSNPAnalyzer server is available at
  31. pmc Discovering and visualizing indirect associations between biomedical concepts
    Yoshimasa Tsuruoka
    School of Information Science, Japan Advanced Institute of Science and Technology JAIST, Nomi, Japan
    Bioinformatics 27:i111-9. 2011
    ..Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner...
  32. pmc Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites
    Amy L Bauer
    Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
    PLoS Comput Biol 6:e1001007. 2010
    ..SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate...
  33. ncbi Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure
    Jiangning Song
    Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia
    Bioinformatics 23:3147-54. 2007
    ..Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications...
  34. ncbi Using a shallow linguistic kernel for drug-drug interaction extraction
    Isabel Segura-Bedmar
    Computer Science Department, Carlos III University of Madrid, Leganes, Spain
    J Biomed Inform 44:789-804. 2011
    ..Our study confirms that the shallow linguistic kernel outperforms our previous pattern-based approach. Additionally, it is our hope that the DrugDDI corpus will allow researchers to explore new solutions to the DDI extraction problem...
  35. pmc Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs)
    Christian Rausch
    Center for Bioinformatics Tübingen ZBIT, University of Tubingen, Germany
    Nucleic Acids Res 33:5799-808. 2005
    ..None of the predictive methods could infer any specificity for 2.4% of the sequences, suggesting completely new types of specificity...
  36. pmc Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest
    Usman Roshan
    Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA
    Nucleic Acids Res 39:e62. 2011
    ..Software and webserver are available at
  37. pmc All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
    Antti Airola
    Turku Centre for Computer Science TUCS and the Department of IT, University of Turku, Joukahaisenkatu 3 5, 20520 Turku, Finland
    BMC Bioinformatics 9:S2. 2008
    ..In contrast to earlier approaches to PPI extraction, the introduced all-paths graph kernel has the capability to make use of full, general dependency graphs representing the sentence structure...
  38. ncbi Inter-species normalization of gene mentions with GNAT
    Jörg Hakenberg
    Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA
    Bioinformatics 24:i126-132. 2008
  39. ncbi Knowledge discovery by automated identification and ranking of implicit relationships
    Jonathan D Wren
    Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm 106, Norman, OK 73019, USA
    Bioinformatics 20:389-98. 2004
  40. ncbi Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning
    Qing Hai Ye
    Liver Cancer Institute and Zhongshan Hospital, Fudan University, Shanghai, China
    Nat Med 9:416-23. 2003
    ..Thus, osteopontin acts as both a diagnostic marker and a potential therapeutic target for metastatic HCC...
  41. pmc An application of Random Forests to a genome-wide association dataset: methodological considerations & new findings
    Benjamin A Goldstein
    Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
    BMC Genet 11:49. 2010
    ..One such approach is the Random Forests (RF) algorithm. The use of RF for SNP discovery related to human disease has grown in recent years; however, most work has focused on small datasets or simulation studies which are limited...
  42. ncbi The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text
    Thomas C Rindflesch
    Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, 8600 Rockville Pike, Bethesda, MD 20894, USA
    J Biomed Inform 36:462-77. 2003
    ..The approach has the potential to support a range of applications, including information retrieval and ontology engineering...
  43. ncbi Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy
    Xiaowei Chen
    HCNR Center for Bioinformatics, Harvard Medical School, Boston, MA 02115, USA
    IEEE Trans Biomed Eng 53:762-6. 2006
    ..Experimental results show that the proposed method is efficient and effective in cell tracking and phase identification...
  44. pmc A feature-based approach to modeling protein-protein interaction hot spots
    Kyu il Cho
    Department of Bio and Brain Engineering, KAIST, 305 701, Daejeon, South Korea
    Nucleic Acids Res 37:2672-87. 2009
    ..Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions...
  45. ncbi A hidden Markov model for predicting transmembrane helices in protein sequences
    E L Sonnhammer
    National Center for Biotechnology Information, NLM NIH, Bethesda, Maryland 20894, USA
    Proc Int Conf Intell Syst Mol Biol 6:175-82. 1998
    ..The same accuracy was achieved on a larger dataset of 160 proteins. These results compare favourably with existing methods...
  46. ncbi Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier
    Malik Yousef
    The Wistar Institute, Philadelphia, PA 19104, USA
    Bioinformatics 22:1325-34. 2006
    ..The resulting algorithm exhibits higher specificity and similar sensitivity compared to currently used algorithms that rely on conserved genomic regions to decrease the rate of FPs...
  47. ncbi Robust face recognition via sparse representation
    John Wright
    Coordinated Science Laboratory, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
    IEEE Trans Pattern Anal Mach Intell 31:210-27. 2009
    ..We conduct extensive experiments on publicly available databases to verify the efficacy of the proposed algorithm and corroborate the above claims...
  48. pmc Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
    Maria Pamela C David
    Virtual Laboratory of Biomolecular Structures, Marine Science Institute, College of Science, University of the Philippines Diliman, Quezon City 1101, Philippines
    BMC Bioinformatics 11:79. 2010
    ..We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences...
  49. ncbi Classifying spatial patterns of brain activity with machine learning methods: application to lie detection
    C Davatzikos
    Department of Radiology, University of Pennsylvania, 3600 Market Street, Suite 380, Philadelphia, PA 19104, USA
    Neuroimage 28:663-8. 2005
  50. ncbi Distilling free-form natural laws from experimental data
    Michael Schmidt
    Computational Biology, Cornell University, Ithaca, NY 14853, USA
    Science 324:81-5. 2009
    ..The discovery rate accelerated as laws found for simpler systems were used to bootstrap explanations for more complex systems, gradually uncovering the "alphabet" used to describe those systems...
  51. ncbi Computational cluster validation in post-genomic data analysis
    Julia Handl
    School of Chemistry, University of Manchester, Faraday Building, Sackville Street, PO Box 88, Manchester M60 1QD, UK
    Bioinformatics 21:3201-12. 2005
    ..Suitable computational cluster validation techniques are available in the general data-mining literature, but have been given only a fraction of the same attention in bioinformatics...
  52. ncbi Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs
    Artem Cherkasov
    Centre for Microbial Diseases and Immunity Research, University of British Columbia, 2259 Lower Mall Research Station, Vancouver, British Columbia V6T 1Z3, Canada
    ACS Chem Biol 4:65-74. 2009
  53. ncbi Support vector machine classification and validation of cancer tissue samples using microarray expression data
    T S Furey
    Department of Computer Science, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
    Bioinformatics 16:906-14. 2000
    ..This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results...
  54. ncbi Data mining in bioinformatics using Weka
    Eibe Frank
    Department of Computer Science, University of Waikato, Private Bag 3105, Hamilton, New Zealand
    Bioinformatics 20:2479-81. 2004
    ..Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it...
  55. pmc APOLLO: a quality assessment service for single and multiple protein models
    Zheng Wang
    Department of Computer Science, University of Missouri, Columbia, MO 65211, USA
    Bioinformatics 27:1715-6. 2011
    ..671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure...
  56. ncbi Improving the prediction of disulfide bonds in Eukaryotes with machine learning methods and protein subcellular localization
    Castrense Savojardo
    Biocomputing Group, University of Bologna, CIRI Life Science and Health Technologies and Department of Biology, Via San Giacomo 9 2, Bologna, Italy
    Bioinformatics 27:2224-30. 2011
    ..Several methods are available to predict cysteine-bonding state and connectivity patterns. However, none of them takes into consideration the relevance of protein subcellular localization...
  57. ncbi Semi-supervised learning for peptide identification from shotgun proteomics datasets
    Department of Genome Sciences, University of Washington, 1705 NE Pacific St, William H Foege Building, Seattle, Washington 98195, USA
    Nat Methods 4:923-5. 2007
  58. pmc Sequence feature-based prediction of protein stability changes upon amino acid substitutions
    Shaolei Teng
    Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
    BMC Genomics 11:S5. 2010
  59. ncbi Graph-based methods for analysing networks in cell biology
    Tero Aittokallio
    Systems Biology Group, Institut Pasteur, 25 28 Rue du Dr Roux, FR 75724 Paris, France
    Brief Bioinform 7:243-55. 2006
    ..Finally, we highlight some challenges in the field and offer our personal view of the key future trends and developments in graph-based analysis of large-scale datasets...
  60. pmc A random forest approach to the detection of epistatic interactions in case-control studies
    Rui Jiang
    MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST Department of Automation, Tsinghua University, Beijing 100084, PR China
    BMC Bioinformatics 10:S65. 2009
    ..It is therefore indispensable to develop new methods that are able to reduce the search space for epistatic interactions from an astronomic number of all possible combinations of genetic variants to a manageable set of candidates...
  61. pmc Activity inference for Ambient Intelligence through handling artifacts in a healthcare environment
    Francisco E Martínez-Pérez
    Facultad de Ingenieria, Universidad Autonoma de Baja California, Km 103 Carretera Tijuana Ensenada, Ensenada, B C 022860, Mexico
    Sensors (Basel) 12:1072-99. 2012
    ..We discuss how the use of RBs might positively impact the problems faced by designers and developers for recovering information in an easier manner and thus they can develop tools focused on the user...
  62. pmc Efficient siRNA selection using hybridization thermodynamics
    Zhi John Lu
    Department of Biochemistry and Biophysics and Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 601 Elmwood Avenue, Box 712, Rochester, NY 14642, USA
    Nucleic Acids Res 36:640-7. 2008
    ..1% by adding equilibrium terms to 25 local sequence features. Prediction of hybridization affinity using partition functions is now available in the RNAstructure software package...
  63. ncbi Ensemble machine learning on gene expression data for cancer classification
    Aik Choon Tan
    Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK
    Appl Bioinformatics 2:S75-83. 2003
    ..We have observed that ensemble learning (bagged and boosted decision trees) often performs better than single decision trees in this classification task...
  64. ncbi A novel ensemble machine learning for robust microarray data classification
    Yonghong Peng
    Department of Computing, University of Bradford, West Yorkshire BD7 1DP, UK
    Comput Biol Med 36:553-73. 2006
  65. pmc EFICAz2: enzyme function inference by a combined approach enhanced by machine learning
    Adrian K Arakaki
    Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia 30318, USA
    BMC Bioinformatics 10:107. 2009
    ..To improve EFICAz's performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment...
  66. ncbi A machine-learning approach for predicting B-cell epitopes
    Nimrod D Rubinstein
    Department of Cell Research and Immunology, Tel Aviv University, Tel Aviv 69978, Israel
    Mol Immunol 46:840-7. 2009
    ..We compare our method to other available tools that perform the same task and show that it outperforms them...
  67. ncbi A reference ontology for biomedical informatics: the Foundational Model of Anatomy
    Cornelius Rosse
    Departments of Biological Structure, and Medical Education and Biomedical Informatics, Structural Informatics Group, University of Washington, Seattle, WA 98195, USA
    J Biomed Inform 36:478-500. 2003
  68. ncbi SOLpro: accurate sequence-based prediction of protein solubility
    Christophe N Magnan
    Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA, USA
    Bioinformatics 25:2200-7. 2009
  69. ncbi Causal protein-signaling networks derived from multiparameter single-cell data
    Karen Sachs
    Biological Engineering Division, Massachusetts Institute of Technology MIT, Cambridge, MA 02139, USA
    Science 308:523-9. 2005
    ..Reconstruction of network models from physiologically relevant primary single cells might be applied to understanding native-state tissue signaling biology, complex drug actions, and dysfunctional signaling in diseased cells...
  70. ncbi Literature mining and database annotation of protein phosphorylation using a rule-based system
    Z Z Hu
    Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA
    Bioinformatics 21:2759-65. 2005
    ..While of great value, such information is limited in databases owing to the laborious process of literature-based curation. Computational literature mining holds promise to facilitate database curation...
  71. pmc Testing computational prediction of missense mutation phenotypes: functional characterization of 204 mutations of human cystathionine beta synthase
    Qiong Wei
    Program in Molecular and Translational Medicine, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, Pennsylvania 19111, USA
    Proteins 78:2058-74. 2010
  72. ncbi Boosting classifier for predicting protein domain structural class
    Kai Yan Feng
    Imaging Science and Biomedical Engineering, Medical School, The University of Manchester, Manchester, M13 9PT, UK
    Biochem Biophys Res Commun 334:213-7. 2005
    ..It is anticipated that LogitBoost can also become a useful vehicle in classifying other attributes of proteins according to their sequences, such as subcellular localization and enzyme family class, among many others...
  73. pmc Prediction of protein-protein interaction sites in sequences and 3D structures by random forests
    Mile Sikić
    Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
    PLoS Comput Biol 5:e1000278. 2009
    ..Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information...
  74. pmc Predicting RNA-binding sites of proteins using support vector machines and evolutionary information
    Cheng Wei Cheng
    Institute of Information Systems and Applications, National Tsing Hua University, Hsinchu, Taiwan
    BMC Bioinformatics 9:S6. 2008
    ..Extensive studies of RNA-binding site prediction have led to the development of several methods. However, they could yield low sensitivities in trade-off for high specificities...
  75. ncbi Machine learning approaches for prediction of linear B-cell epitopes on proteins
    Johannes Sollner
    Intercell AG, Campus Vienna Biocenter 6, A 1030 Vienna, Austria
    J Mol Recognit 19:200-8. 2006
    ..The major finding is that machine learning classifiers clearly outperform the reference classification systems on the HIV epitope validation set...
  76. ncbi Support vector machine-based classification of Alzheimer's disease from whole-brain anatomical MRI
    Benoît Magnin
    UMR S 678, INSERM, Paris, France
    Neuroradiology 51:73-83. 2009
  77. ncbi Event extraction with complex event classification using rich features
    Makoto Miwa
    Department of Computer Science, University of Tokyo, Hongo 7 3 1, Bunkyo ku, Tokyo, Japan
    J Bioinform Comput Biol 8:131-46. 2010
    ..The proposed complex (binding and regulation) event detector outperforms the best system from the BioNLP'09 shared task challenge...
  78. pmc Identifying and tracking pedestrians based on sensor fusion and motion stability predictions
    Basam Musleh
    Intelligent Systems Laboratory, Universidad Carlos III de Madrid Avda de la Universidad 30, 28911 Leganes, Madrid, Spain
    Sensors (Basel) 10:8028-53. 2010
    ..The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle...
  79. ncbi Machine learning in virtual screening
    James L Melville
    School of Chemistry, University of Nottingham, University Park, Nottingham, UK
    Comb Chem High Throughput Screen 12:332-43. 2009
    ..Effective application of these methodologies requires an appreciation of data preparation, validation, optimization, and search methodologies, and we also survey developments in these areas...
  80. pmc High accuracy information extraction of medication information from clinical notes: 2009 i2b2 medication extraction challenge
    Jon Patrick
    Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
    J Am Med Inform Assoc 17:524-7. 2010
    ..Medication information comprises a most valuable source of data in clinical records. This paper describes use of a cascade of machine learners that automatically extract medication information from clinical records...
  81. pmc Lancet: a high precision medication event extraction system for clinical text
    Zuofeng Li
    College of Health Sciences, University of Wisconsin Milwaukee, Wisconsin, USA
    J Am Med Inform Assoc 17:563-7. 2010
  82. pmc Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans
    Maria D Chikina
    Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA
    PLoS Comput Biol 5:e1000417. 2009
    ..To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data...
  83. ncbi Sequence complexity of disordered protein
    P Romero
    School of Electrical Engineering and Computer Science, Washington State University, Pullman, Washington 99164 4660, USA
    Proteins 42:38-48. 2001
  84. pmc Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces
    Zheng Xia
    Bioinformatics and Bioengineering Program, The Methodist Hospital Research Institute, Weill Medical College, Cornell University, Houston, TX 77030, USA
    BMC Syst Biol 4:S6. 2010
    ..Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data...
  85. pmc Adaptive decoding for brain-machine interfaces through Bayesian parameter updates
    Zheng Li
    Department of Neurobiology and Center for Neuroengineering, Duke University, Durham, NC 27710, U S A
    Neural Comput 23:3162-204. 2011
    ..These results indicate that Bayesian regression self-training can maintain BMI control accuracy over long periods, making clinical neuroprosthetics more viable...
  86. pmc Drug side effect extraction from clinical narratives of psychiatry and psychology patients
    Sunghwan Sohn
    Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA
    J Am Med Inform Assoc 18:i144-9. 2011
    ..To extract physician-asserted drug side effects from electronic medical record clinical narratives...
  87. ncbi POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties
    Chun Wei Tung
    Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan
    Bioinformatics 23:942-9. 2007
    ..This study focuses on mining informative physicochemical properties from known experimental immunogenicity data to understand immune responses and predict immunogenicity of MHC-binding peptides accurately...
  88. ncbi Pattern recognition in bioinformatics
    Dick de Ridder
    Delft Bioinformatics Lab, Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands Tel 31 15 2785114 Fax 31 15 2787022
    Brief Bioinform 14:633-47. 2013
    ..We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained. ..
  89. ncbi Face description with local binary patterns: application to face recognition
    Timo Ahonen
    Machine Vision Group, Department of Electrical Information Engineering, University of Oulu, Finland
    IEEE Trans Pattern Anal Mach Intell 28:2037-41. 2006
    ..The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed...
  90. pmc Exploiting nonlinear recurrence and fractal scaling properties for voice disorder detection
    Max A Little
    Systems Analysis, Modelling and Prediction Group, Department of Engineering Science, University of Oxford, Oxford, UK
    Biomed Eng Online 6:23. 2007
    ..Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness...
  91. ncbi PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs
    Ping Xuan
    Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, PR China
    Bioinformatics 27:1368-76. 2011
    ..Therefore, it is essential to develop a method based on machine learning to classify real plant pre-miRNAs and pseudo genome hairpins...
  92. pmc Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study
    Jonathan Q Jiang
    School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, PR China
    BMC Bioinformatics 13:S20. 2012
    ..However, so far, only a few efforts based on heuristic rules have been made in this regard...
  93. pmc Meeting people's needs in a fully interoperable domotic environment
    Vittorio Miori
    Institute of Information Science and Technologies A Faedo ISTI, CNR National Research Council of Italy, Pisa, Italy
    Sensors (Basel) 12:6802-24. 2012
  94. ncbi The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression
    James W F Catto
    Academic Urology Unit, University of Sheffield, Sheffield, United Kingdom
    Eur Urol 57:398-406. 2010
    ..Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret...
  95. ncbi Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks
    James W F Catto
    The Academic Urology Unit, Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S10 2JF, United Kingdom
    Clin Cancer Res 9:4172-7. 2003
    ..b>Artificial intelligence (AI) may provide these suitable methods...
  96. ncbi Lysine acetylation sites prediction using an ensemble of support vector machine classifiers
    Yan Xu
    College of Science, China Agricultural University, Beijing 100083, China
    J Theor Biol 264:130-5. 2010
    ..The resulting method has been implemented in EnsemblePail, a web server for lysine acetylation sites prediction available at
  97. pmc Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning
    Zhuoran Wang
    Department of Computer Science, University College London, London, United Kingdom
    PLoS ONE 7:e30412. 2012
    ..Electronic health records are invaluable for medical research, but much of the information is recorded as unstructured free text which is time-consuming to review manually...
  98. ncbi Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
    Peter Mondrup Rasmussen
    DTU Informatics, Technical University of Denmark, Denmark
    Neuroimage 55:1120-31. 2011
  99. pmc Sparse bayesian learning for identifying imaging biomarkers in AD prediction
    Li Shen
    Center for Neuroimaging, Department of Radiology and Imaging Sciences, USA
    Med Image Comput Comput Assist Interv 13:611-8. 2010
    ..While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures...
  100. pmc Discriminative and informative features for biomolecular text mining with ensemble feature selection
    Sofie Van Landeghem
    Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium
    Bioinformatics 26:i554-60. 2010
    ..This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results...
  101. pmc Computational models for in-vitro anti-tubercular activity of molecules based on high-throughput chemical biology screening datasets
    Vinita Periwal
    GN Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology CSIR, New Delhi 110007, India
    BMC Pharmacol 12:1. 2012
    ..In addition, this approach would save significantly on the cost, effort and time required to run high throughput screens...

Research Grants62

    JEFFREY SCOTT BARRETT; Fiscal Year: 2010
    ..This guidance will have the opportunity to grow (artificial intelligence) as patient diversity expands the historical experience (population priors) with an agent or combination ..
  2. Image analysis for high-throughput C. elegans infection and metabolism assays
    CAROLINA EWA ASA WAHLBY; Fiscal Year: 2013
    ..experts in model-based segmentation and statistical image analysis at MIT's Computer Science and Artificial Intelligence Laboratory, and with Anne Carpenter, developer of open-source image analysis software at the Broad ..
  3. Multi-source clinical Question Answering system
    Guergana Savova; Fiscal Year: 2010
    ..Develop artificial intelligence and information retrieval approaches that allow a clinician or researcher confronting complex patient ..
  4. An Interactive Video Game for HIV Prevention in At-Risk Adolescents
    LYNN ELIZABETH FIELLIN; Fiscal Year: 2013
    ..development, social cognitive theory and self-efficacy, prospect theory and message framing, software and artificial intelligence development, and commercial game design...
  5. Speech Therapy Robot (STR) to assist in the administration of evidence based spee
    Garima Srivastava; Fiscal Year: 2011
    ..STR will use biologically plausible artificial intelligence models to prototype a system that is affordable, easy to use, portable and extensible to work with any ..
  6. A computer model to improve breast cancer diagnosis
    Elizabeth S Burnside; Fiscal Year: 2010
    ..follow a career development plan that consists of 1) acquisition of advanced research competencies in artificial intelligence, machine learning algorithms, probability theory, Bayesian reasoning, research ethics, and clinical trial ..
  7. Optimal neural and behavioral markers for learning to learn during infancy
    Rachel Wu; Fiscal Year: 2013
    ..The findings will benefit researchers within the larger community of developmental science, as well as artificial intelligence, perceptual learning, education, animal learning, machine learning, and evolutionary psychology...
  8. Automated Integration of Biomedical Knowledge
    Gil Alterovitz; Fiscal Year: 2010
    ..project brings together a unique group of competences, ranging from ontology engineering, statistics, artificial intelligence, bioinformatics, cancer research, and clinical pharmacogenomics, to develop a principled method, grounded ..
  9. Advanced Computational Framework for Decision Support in Critically Ill Children
    Randall C Wetzel; Fiscal Year: 2010
    ..Abstract: Artificial Intelligence (AI) and advanced computational techniques, applied to complex, multidimensional, streaming, clinical ..
  10. ISMB 2012 Conference Support for Students &Young Scientists
    THERESA GAASTERLAND; Fiscal Year: 2012
    ..horizon of future discoveries, but is distinguished from many other events in computational biology or artificial intelligence by an insistence that the researchers work with real molecular biology data, not theoretical or toy ..
  11. Passive Activity Monitoring with Patient Identification and Gesture Detection
    JAMES L WOLF; Fiscal Year: 2012
    ..By applying the latest monitoring and artificial intelligence technologies, the outcomes of this research would enable the Ingenium Care system to improve the quality ..
    Jason E Owen; Fiscal Year: 2011
    ..and others and has significance for the fields of medicine, psychology, computational linguistics, and artificial intelligence. PUBLIC HEALTH RELEVANCE: Identifying specific emotional, cognitive, and behavioral factors that ..
  13. Artificial Intelligence in a Mobile Intervention for Depression (AIM)
    DAVID CURTIS MOHR; Fiscal Year: 2013
    ..Machine learning, a branch of artificial intelligence, focuses on the development of algorithms that automatically improve and evolve based on collected data...
  14. Predicting Patient Instability Noninvasively for Nursing Care (PPINNC)
    Michael R Pinsky; Fiscal Year: 2013
    ..One data-driven CDSS approach uses an artificial intelligence type called "machine learning" to evaluate moving-time series data and learn data patterns leading to an ..
  15. Feasibility Trial of a Problem-Solving Weight Loss Mobile Application
    Bengisu Tulu; Fiscal Year: 2013
    ..Using principles of "artificial intelligence" we will convert the algorithm of problem solving counseling into the mobile application so that it may ..
  16. Intelligent and Automatic Image Segmentation Software for High ThroughputAnalysi
    Karyn Esser; Fiscal Year: 2013
    ..image analysis software package for skeletal muscle tissue;2) Develop a novel online updated intelligent artificial intelligence unit to enable the software to learn from errors;3) Build a novel high performance computing unit to ..
  17. Microbial Diversity and Genetic Characterization of Cariogenic Biofilms
    Page W Caufield; Fiscal Year: 2012
    ..Using the power of multiple test analyses derived artificial intelligence programming;biomarkers will be used as the basis for a modeling algorithm capable of classifying strains ..
  18. Preventing Drug Abuse among Hispanic Adolescents
    STEVEN PAUL SCHINKE; Fiscal Year: 2013
    ..Through a human simulation interaction platform, the program will employ artificial intelligence, graphic portrayals of emotional states, and a branched learning environment in which youths can acquire, ..
    Mriganka Sur; Fiscal Year: 2013
    ..and cognitive science, combined with the theoretical strength of computational neuroscience and artificial intelligence. Trainees begin laboratory work through lab rotations in the first two terms and subsequently join a ..
  20. Building motif lexicons
    Martin R Schiller; Fiscal Year: 2010
    ..2) To build a more comprehensive motif database we will use artificial intelligence to mine PubMed...
  21. Temporal relation discovery for clinical text
    Guergana K Savova; Fiscal Year: 2013
    ..Processing free text poses a number of challenges to which the fields of Artificial intelligence, natural language processing and computer science in general have made advances...
  22. Intonation in spontaneous English & Japanese dialogue
    Shari R Speer; Fiscal Year: 2010
    ..processing and development, but also for accurate speech identification and generation systems in artificial intelligence, and for the development of effective diagnoses and therapies for aphasic patients and others with ..
  23. Efficient software and algorithms for analyzing markers data on general pedigree
    RINA DECHTER; Fiscal Year: 2010
    ..will consist of novel algorithms that extend state of the art algorithms from graph theory, statistics, artificial intelligence, and genetics. This tool will enhance capabilities to analyze genetic components of inherited diseases...
    John Clarke; Fiscal Year: 1993
    ..The objective is to rigorously evaluate a recently developed artificial intelligence decision aid to improve the initial definitive management of patients with injuries, specifically to ..
    SUZANNE MARCH; Fiscal Year: 2009
    ..A prototype system using artificial intelligence techniques has been successfully developed to extract reports of CNS neoplasms from CT and MRI reports...
    Peter Santago; Fiscal Year: 2001
    ..To improve our polyp detection algorithm with expanded feature analysis and artificial intelligence methods; 3...
    WILMA OLSON; Fiscal Year: 2003
    ..Levy, Gerald S. Manning, Wilma K. Olson), artificial intelligence (Casimir A. Kulikowski, Martin Farach), continuum mechanics (Bernard D...
  28. Neuromotor Modeling of Adductor Spasmodic Dysphonia
    Rick Roark; Fiscal Year: 2009
    ..In applying recent advances in multi-dimensional physiologic and artificial intelligence technologies, this project will formulate models of vocal motor control at the level of the brainstem ..
    Peter Szolovits; Fiscal Year: 1992
    Casimir Kulikowski; Fiscal Year: 1991
    ..general objective of the Rutgers Resource is to apply advanced methods of computer science, particularly artificial intelligence, to problems of biomedical research and practice...
    Antonie van den Bogert; Fiscal Year: 2006
    ..Reinforcement learning (RL) is a technique from artificial intelligence that has the potential to overcome this problem...
    NICHOLAS DE CLARIS; Fiscal Year: 1991 providing powerful new methodologies for data analysis and presentation, mathematical computation, artificial intelligence, and high speed communication; 2) allowing maximum resource sharing among all investigators while, at the ..
  33. Automated (AI) Analysis of Sleep Disordered Breathing
    Indu Ayappa; Fiscal Year: 2004 the research program and expose her to aspects of clinical research in sleep, neural science and artificial intelligence techniques. She will be mentored by David Rapoport, M.D., Joyce Walsleben, Ph.D., and Maurice Ohayon, M.D...
  34. The gist of the space: A space centered approach to visual scene perception
    Aude Oliva; Fiscal Year: 2013
    ..Real-world scene recognition is an unsolved mystery that will have implications for neuroscience, computational vision, artificial intelligence, robotics and psychology.
  35. Accessible Artificial Intelligence Tutoring Software
    BENNY JOHNSON; Fiscal Year: 2005
    Quantum has successfully developed, tested and brought to the classroom the first artificial intelligence (Al) tutoring systems in chemistry education...
  36. Artificial Intelligence Methods for Crystallization
    JOHN ROSENBERG; Fiscal Year: 2007
    ..III. Improving the "user friendliness," integration and automation of the entire system. ..
    JOSEPH GARTNER; Fiscal Year: 2000
    ..rules in the American Psychiatric Association Diagnostic and Statistical Manual (DSM-IV) uses and artificial intelligence engine ("XSB") to implement the logic of DSM-IV along with and an interactive graphical user interface to ..
    STEPHEN KLYCE; Fiscal Year: 2006
    ..2) Refine artificial intelligence methods for the classification and interpretation of corneal topography and ocular wavefront data with ..
  39. Data Mining to Identify Motor Fluctuations in PD
    Paolo Bonato; Fiscal Year: 2006
    DESCRIPTION (provided by applicant): The purpose of this project is to develop data mining and artificial intelligence systems to recognize the presence and severity of motor fluctuations in patients with Parkinson's disease (PD)...
    J Beck; Fiscal Year: 1990
    ..Methods to be employed in the development of the system will arise from decision theory, artificial intelligence, and software engineering...
  41. A Laser-Based Device for Work Site Stability Assessment
    Xiaoqing Sun; Fiscal Year: 2007
    ..This new device will take advantage of innovations in laser ultrasonics, artificial intelligence (Al) and advanced acoustic emission technology to provide mine workers with a unique instant, real time ..
    DANIEL HIER; Fiscal Year: 1990
    Expert systems represents a branch of artificial intelligence that deals with computer program solutions to problems normally solved by human experts...
    JACQUELINE HAYNES; Fiscal Year: 1993
    The proposed research will apply state-of-the-art computer technology in digital sound, voice recognition, artificial intelligence, and graphical user interfaces to enhance the administration and scoring of a projective test which ..
  44. LiFESim: Software for health science education (NCRR)
    CHARLES EARL; Fiscal Year: 2004
    ..We will complement simulation-based learning with two other artificial intelligence based methodologies - the use of lifelike pedagogical agents, and the use of case-based reasoning...
  45. Development of Ultrasonic Appratus for Dental Diagnosis
    Xiaoqing Sun; Fiscal Year: 2004
    ..Ultrasonic responses of the tooth structure will be analyzed by a pattern recognition expert system (artificial intelligence) to determine the diagnosis of the tooth inspected...
    Mark Perlin; Fiscal Year: 1991
    ..Specifically, we propose to accomplish the following research: 1. Using existing methods of artificial intelligence and knowledge engineering, construct a first prototype expert system...
    James Duncan; Fiscal Year: 1992
    ..The proposed system design is influenced by current artificial intelligence and image understanding technologies, but remains firmly grounded in more classical mathematical and ..
    DOV KAUFMAN; Fiscal Year: 1990
    ..system, to be developed in the second stage of the project, will include elements of expert systems and artificial intelligence technology...
    Michael Smith; Fiscal Year: 1992
    ..the all-cause mortality risk equations; to enhance the ACMRP by incorporating innovative, new technology (artificial intelligence, CD-ROM, interactive feedback); and to study the impact of the ACMRP, including the new technology, in ..
    GB MANCINI; Fiscal Year: 1990
    b>Artificial intelligence and machine vision systems often use shape analysis as a fundamental approach to characterization of complex objects and motion...
  51. Using AL to Enhance VR Anxiety Disorder Treatment
    TIMOTHY GIFFORD; Fiscal Year: 2002
    DESCRIPTION (provided by applicant) This project will develop an artificial intelligence to provide the core functionality for virtual reality and computer based treatments for anxiety disorders...
  52. A Bioinformatic Approach to Inferring Protein Contacts
    MARCELLA MCCLURE; Fiscal Year: 2005
    ..Instead, a method from the field of artificial intelligence, Bayesian Networks (also known as Belief Networks) will be utilized to correlate the results...
    YUNG MING LURE; Fiscal Year: 1992
    ..In this SBIR project, we would like to (1) explore several artificial intelligence techniques for error-free radiological image compression, (2) evaluate the proposed compression method to ..
    Edward Shortliffe; Fiscal Year: 1991
    ..shared technological resource for health research and 2) the specific encouragement of applications of artificial intelligence in medicine (AIM)...
    Perry Miller; Fiscal Year: 1990
    The proposed research will continue our exploration of the critiquing approach to bringing artificial intelligence (AI) based advice to the practicing physician...
  56. Attractors of Complex Signal Transduction Systems
    JIMMY ROGERS; Fiscal Year: 2004
    ..The most advanced techniques in the field of chaos theory and neural networks (the basis of artificial intelligence) will be applied to determine whether biochemical signal transduction systems have the fundamental ..
  57. Molecular Analysis of Human Breast Cancer
    Robert Clarke; Fiscal Year: 2007
    ..Our multidisciplinary teams will use these molecular profiles and established prognostic factors to build artificial intelligence-based classifiers and multivariate models that accurately predict those patients with nonmetastatic ..
    Jack Smith; Fiscal Year: 1991
    ..As part of this refinement process, techniques and methodologies of artificial intelligence will be used to investigate the problem-solving of experts in the diagnosis of liver disease...
    RICHARD STOTTLER; Fiscal Year: 1991
    ..Neural networks are a very recent outgrowth of the Artificial Intelligence field. They offer fault tolerant, adaptable, parallel computation...
  60. Educational Tools for Neuroscience
    ERIC DOMESHEK; Fiscal Year: 2001
    ..Intelligent Tutoring Systems (ITS) are an emerging educational technology based on artificial intelligence research...
  61. Development of Ultrasonic Apparatus for Dental Diagnosis
    Xiaoqing Sun; Fiscal Year: 2001
    ..Ultrasonic responses of the tooth structure will then be analyzed by a pattern recognition expert system (artificial intelligence) to determine the diagnosis of the tooth inspected...
    John Schroeder; Fiscal Year: 1991
    ..Recent progress has been made by application of artificial intelligence techniques to examine structural correlates of function and to ascertain relationships between known ..