fuzzy logic

Summary

Summary: Approximate, quantitative reasoning that is concerned with the linguistic ambiguity which exists in natural or synthetic language. At its core are variables such as good, bad, and young as well as modifiers such as more, less, and very. These ordinary terms represent fuzzy sets in a particular problem. Fuzzy logic plays a key role in many medical expert systems.

Top Publications

  1. ncbi Rough-fuzzy collaborative clustering
    Sushmita Mitra
    Machine Intelligence Unit, Indian Statistical Institute, Kolkata
    IEEE Trans Syst Man Cybern B Cybern 36:795-805. 2006
  2. ncbi Designing stable MIMO fuzzy controllers
    Eric Kubica
    IEEE Trans Syst Man Cybern B Cybern 35:372-80. 2005
  3. ncbi FCMAC-BYY: fuzzy CMAC using Bayesian Ying-Yang learning
    Minh Nhut Nguyen
    Centre for Computational Intelligence, School of Computer Engineering, Nanyang Technological University, 639798 Singapore
    IEEE Trans Syst Man Cybern B Cybern 36:1180-90. 2006
  4. ncbi GFAM: evolving Fuzzy ARTMAP neural networks
    Ahmad Al-Daraiseh
    School of EECS, University of Central Florida, Orlando, FL 32816 2786, United States
    Neural Netw 20:874-92. 2007
  5. ncbi Logic-based models for the analysis of cell signaling networks
    Melody K Morris
    Center for Cell Decision Process and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
    Biochemistry 49:3216-24. 2010
  6. ncbi A climate-based distribution model of malaria transmission in sub-Saharan Africa
    M H Craig
    National Malaria Research Programme, South African Medical Research Council, PO Box 17120, Congella, Durban 4013, South Africa
    Parasitol Today 15:105-11. 1999
  7. ncbi A system for brain tumor volume estimation via MR imaging and fuzzy connectedness
    Jianguo Liu
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, 4th Floor, Blockley Hall, 423 Guardian Drive, PA 19104-6021, USA
    Comput Med Imaging Graph 29:21-34. 2005
  8. ncbi Automatic glioma characterization from dynamic susceptibility contrast imaging: brain tumor segmentation using knowledge-based fuzzy clustering
    Kyrre E Emblem
    Department of Medical Physics, Rikshospitalet University Hospital, Oslo, Norway
    J Magn Reson Imaging 30:1-10. 2009
  9. ncbi Classification of EMG signals using neuro-fuzzy system and diagnosis of neuromuscular diseases
    Sabri Koçer
    Department of Electronic and Computer Education, Faculty of Technical Education, Gazi University, Ankara, Turkey
    J Med Syst 34:321-9. 2010
  10. ncbi From vagueness in medical thought to the foundations of fuzzy reasoning in medical diagnosis
    Rudolf Seising
    Section on Medical Expert and Knowledge Based Systems, Core Unit for Medical Statistics and Informatics, Medical University of Vienna, Spitalgasse 23, A 1090 Vienna, Austria
    Artif Intell Med 38:237-56. 2006

Research Grants

  1. A BREATH TEST FOR LUNG CANCER
    Michael Phillips; Fiscal Year: 2007
  2. Multifunction Prosthesis Control using Implanted Sensors
    Richard Weir; Fiscal Year: 2007
  3. PORTABLE DEFIBRILLATOR FUZZY-LOGIC-BASED BATTERY METER
    Pritpal Singh; Fiscal Year: 2003
  4. Automatic Detection of Critical Dermoscopy Features for Melanoma Diagnosis
    William Stoecker; Fiscal Year: 2007
  5. Detection of chewing and swallowing to estimate eating patterns and energy intake
    Edward Sazonov; Fiscal Year: 2006
  6. PHASE RESETTING AND SENSORY INHIBITION IN THE CNS
    Nashaat Boutros; Fiscal Year: 1999
  7. PHASE RESETTING AND SENSORY INHIBITION IN THE CNS
    Nashaat Boutros; Fiscal Year: 2005
  8. BIOPHYSICAL STUDIES OF FOLDING MUTANTS OF STAPH NUCLEASE
    David Shortle; Fiscal Year: 1999
  9. VOLATILE MARKERS OF ORAL MALODOR IN THE BREATH
    Michael Phillips; Fiscal Year: 2004
  10. VOLATILE MARKERS OF PULMONARY TUBERCULOSIS IN THE BREATH
    Michael Phillips; Fiscal Year: 2006

Detail Information

Publications305 found, 100 shown here

  1. ncbi Rough-fuzzy collaborative clustering
    Sushmita Mitra
    Machine Intelligence Unit, Indian Statistical Institute, Kolkata
    IEEE Trans Syst Man Cybern B Cybern 36:795-805. 2006
    ..A detailed clustering algorithm is developed by integrating the advantages of both fuzzy sets and rough sets, and a measure of quantitative analysis of the experimental results is provided for synthetic and real-world data...
  2. ncbi Designing stable MIMO fuzzy controllers
    Eric Kubica
    IEEE Trans Syst Man Cybern B Cybern 35:372-80. 2005
  3. ncbi FCMAC-BYY: fuzzy CMAC using Bayesian Ying-Yang learning
    Minh Nhut Nguyen
    Centre for Computational Intelligence, School of Computer Engineering, Nanyang Technological University, 639798 Singapore
    IEEE Trans Syst Man Cybern B Cybern 36:1180-90. 2006
    ..of the network by a significant degree as compared to the original CMAC; and third, it provides an intuitive fuzzy logic reasoning and has clear semantic meanings...
  4. ncbi GFAM: evolving Fuzzy ARTMAP neural networks
    Ahmad Al-Daraiseh
    School of EECS, University of Central Florida, Orlando, FL 32816 2786, United States
    Neural Netw 20:874-92. 2007
    ..We illustrate that GFAM produces improved results over these architectures, as well as other competitive classifiers...
  5. ncbi Logic-based models for the analysis of cell signaling networks
    Melody K Morris
    Center for Cell Decision Process and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
    Biochemistry 49:3216-24. 2010
    ....
  6. ncbi A climate-based distribution model of malaria transmission in sub-Saharan Africa
    M H Craig
    National Malaria Research Programme, South African Medical Research Council, PO Box 17120, Congella, Durban 4013, South Africa
    Parasitol Today 15:105-11. 1999
    ..Together with population, morbidity and mortality data, the model provides a fundamental tool for strategic control of malaria...
  7. ncbi A system for brain tumor volume estimation via MR imaging and fuzzy connectedness
    Jianguo Liu
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, 4th Floor, Blockley Hall, 423 Guardian Drive, PA 19104-6021, USA
    Comput Med Imaging Graph 29:21-34. 2005
    ..The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system...
  8. ncbi Automatic glioma characterization from dynamic susceptibility contrast imaging: brain tumor segmentation using knowledge-based fuzzy clustering
    Kyrre E Emblem
    Department of Medical Physics, Rikshospitalet University Hospital, Oslo, Norway
    J Magn Reson Imaging 30:1-10. 2009
    ....
  9. ncbi Classification of EMG signals using neuro-fuzzy system and diagnosis of neuromuscular diseases
    Sabri Koçer
    Department of Electronic and Computer Education, Faculty of Technical Education, Gazi University, Ankara, Turkey
    J Med Syst 34:321-9. 2010
    ..Coefficients that were obtained from the EMG signals using Autoregressive (AR) analysis was applied to neuro-fuzzy system. The classification performance of the feature sets was investigated for three classes...
  10. ncbi From vagueness in medical thought to the foundations of fuzzy reasoning in medical diagnosis
    Rudolf Seising
    Section on Medical Expert and Knowledge Based Systems, Core Unit for Medical Statistics and Informatics, Medical University of Vienna, Spitalgasse 23, A 1090 Vienna, Austria
    Artif Intell Med 38:237-56. 2006
    ....
  11. ncbi The application of fuzzy logic to the prescription of antithrombotic agents in the elderly
    Cathy M Helgason
    Department of Neurology, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA
    Drugs Aging 21:731-6. 2004
    ..An alternative approach to capturing the unique context of each patient is based using fuzzy logic and mathematics. In particular, the fuzzy subsethood theorem of Kosko has direct application here...
  12. ncbi Prediction of protein function improving sequence remote alignment search by a fuzzy logic algorithm
    Antonio Gomez
    Institut de Biotecnologia i Biomedicina, Departament de Bioquímica i Biologia Molecular de la, Universitat Autonoma de Barcelona, Bellaterra, Barcelona, 08193, Spain
    Protein J 27:130-9. 2008
    ..that predicts the putative function for the protein integrating the results from the PSI-BLAST program and a fuzzy logic algorithm is described...
  13. ncbi Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient
    Cathy M Helgason
    Department of Neurology, University of Illinois College of Medicine in Chicago, 912 South Wood Street, Room 855 N, Chicago, IL 60612, USA
    Expert Rev Neurother 4:249-54. 2004
    ..This extrapolation is dependent upon the expertise of the physician. A fuzzy logic multivalued-based scientific model allows this expertise to be numerically represented and solves the clinical ..
  14. ncbi Geometric interpretation of gene coexpression network analysis
    Steve Horvath
    Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America
    PLoS Comput Biol 4:e1000117. 2008
    ..The unification of coexpression network methods with traditional data mining methods can inform the application and development of systems biologic methods...
  15. ncbi A fully automated method for quantifying and localizing white matter hyperintensities on MR images
    Minjie Wu
    Department of Electrical and Computer Engineering, University of Pittsburgh, USA
    Psychiatry Res 148:133-42. 2006
    ..Given the emergence of large NeuroImage databases, techniques, such as that described here, will allow for a better understanding of the relationship between WMHs and neuropsychiatric disorders...
  16. ncbi Statistical versus fuzzy measures of variable interaction in patients with stroke
    C M Helgason
    Department of Neurology and Psychiatry, University of Illinois College of Medicine at Chicago, Ill, 60611, USA
    Neuroepidemiology 20:77-84. 2001
    ..A difference in measure of variable interaction in the patient from that in the collective would show how extrapolation of information from the latter to the single patient is counterintuitive...
  17. ncbi Fuzzy Logic in neurosurgery: predicting poor outcomes after lumbar disk surgery in 501 consecutive patients
    Muhammad Shahzad Shamim
    Section of Neurosurgery, Department of Surgery, Aga Khan University Hospital, P O Box 3500, Stadium Road, Karachi 74800, Pakistan
    Surg Neurol 72:565-72; discussion 572. 2009
    ..We have used Fuzzy Logic-based fuzzy inference system (FIS) for identifying patients unlikely to improve after disk surgery and explored ..
  18. ncbi Survey of fuzzy logic applications in brain-related researches
    Omer Faruk Bay
    Department of Electronics and Computer Education, Faculty of Technical Education, Gazi University, Ankara, Turkey
    J Med Syst 27:215-23. 2003
    The aim of this study was to survey fuzzy logic (FL) applications in brain researches...
  19. ncbi Fuzzy logic and decision-making in anaesthetics
    Paul Grant
    Department of Anaesthetics, Timaru Hospital, Queen Street, Timaru, South Canterbury Private Bag 911, New Zealand
    J R Soc Med 98:7-9. 2005
  20. ncbi The use of fuzzy logic to select which curves need to be instrumented and fused in adolescent idiopathic scoliosis: a feasibility study
    Marie Lyne Nault
    Division of Orthopedics, Sainte Justine Hospital, 3175 Cote Sainte Catherine Road, Montreal, Quebec, Canada H3T 1C5
    J Spinal Disord Tech 20:594-603. 2007
    ..Our objective is to capture the proposed rules for the selection of fusion levels and integrate them in a fuzzy logic model to decrease haziness and imprecision in the selection process...
  21. ncbi Probabilistic and fuzzy logic in the clinical diagnosis
    L Pagliaro
    Intern Emerg Med 2:75; discussion 100-6. 2007
  22. ncbi A fuzzy logic-based decision support system on anesthetic depth control for helping anesthetists in surgeries
    Hamdi Melih Saraoğlu
    Department of Electrical and Electronics Engineering, Dumlupinar University, Kutahya, Turkey
    J Med Syst 31:511-9. 2007
    In this study, a fuzzy logic-based anesthetic depth decision support system (ADDSS) was realized for anesthetic depth control to help anesthetists in surgeries...
  23. ncbi Morphology and morphometry in chronic spinal cord injury assessed using diffusion tensor imaging and fuzzy logic
    Benjamin M Ellingson
    Dept of Biomed Eng, Marquette Univ, Milwaukee, WI 53201, USA
    Conf Proc IEEE Eng Med Biol Soc 1:1885-8. 2006
    ..Furthermore, the use of a fuzzy logic algorithm to segment regions of gray and white matter within the spinal cord based on these anisotropy ..
  24. ncbi Fuzzy epidemics
    Eduardo Massad
    School of Public Health and School of Medicine, The University of Sao Paulo, Avenue Dr Arnaldo 455, 01246 903 Sao Paulo, Brazil
    Artif Intell Med 29:241-59. 2003
    The purpose of this paper is to provide a review of the current state of fuzzy logic theory in epidemiology, which is a recent area of research...
  25. ncbi Probabilistic and fuzzy logic in clinical diagnosis
    G Licata
    Department of Clinical Neurosciences, University of Palermo, Via Catania 166, I 90141, Palermo, Italy
    Intern Emerg Med 2:100-6. 2007
    In this study I have compared classic and fuzzy logic and their usefulness in clinical diagnosis...
  26. ncbi Fuzzy logic for elimination of redundant information of microarray data
    Edmundo Bonilla Huerta
    LERIA, Universite d Angers, 2 Boulevard Lavoisier, 49045 Angers, France
    Genomics Proteomics Bioinformatics 6:61-73. 2008
    ..To cope with these difficulties, this paper introduces a fuzzy logic based pre-processing approach composed of two main steps...
  27. ncbi Improving decisionmaking processes with the fuzzy logic approach in the epidemiology of sleep disorders
    M M Ohayon
    Sleep Disorders Center, Stanford University School of Medicine, CA 94305, USA
    J Psychosom Res 47:297-311. 1999
    ..For this purpose, an expert system was developed for the assessment of sleep disorders and endowed with the fuzzy logic capabilities necessary to determine the degree to which a given symptom corresponds to a specific diagnosis...
  28. ncbi Automated classification of multispectral MR images using unsupervised constrained energy minimization based on fuzzy logic
    Geng Cheng Lin
    Department of Electrical Engineering, National Central University, Jhongli, Taiwan, ROC
    Magn Reson Imaging 28:721-38. 2010
    ..Experimental results demonstrate that UCEM segments a multispectral MR image much more effectively than either Functional MRI of the Brain's (FMRIB's) automated segmentation tool or fuzzy C-means does...
  29. ncbi Using fuzzy logic to predict response to citalopram in alcohol dependence
    C A Naranjo
    Psychopharmacology Research Program, Sunnybrook Health Science Centre, Toronto, Ontario, Canada
    Clin Pharmacol Ther 62:209-24. 1997
    ..We hypothesized that fuzzy logic, a qualitative computational approach, could predict response to 40 mg/day citalopram and 40 mg/day citalopram ..
  30. ncbi HPV infection in relation to OSCC histological grading and TNM stage. Evaluation by traditional statistics and fuzzy logic model
    G Campisi
    Dipartimento di Scienze Stomatologiche, Universita di Palermo, Via del Vespro 129, 90127 Palermo, Italy
    Oral Oncol 42:638-45. 2006
    ..between histological grading (HG), TNM clinical stage and HPV infection; and to study the performance of fuzzy logic compared to traditional statistics, in the analysis of HPV status and correlates of OSCC...
  31. ncbi [Video-electroencephalography prolonged monitoring in patients with ambulatory diagnosis of medically refractory temporal lobe epilepsy: application of fuzzy logic's model]
    M E Cosenza-Andraus
    Servicio de Neurologia, Hospital Universitario Clementino Fraga Filho HUCFF, Rio de Janeiro, Brasil
    Rev Neurol 43:7-14. 2006
    ..The fuzzy logic gives an efficient and intelligent analysis method, able to make inferences over ambiguous systems, and has ..
  32. ncbi Fuzzy logic-based tumor-marker profiles improved sensitivity in the diagnosis of lung cancer
    Joachim Schneider
    Institut und Poliklinik für Arbeits und Socialmedizin der Justus Liebig Universität, Giessen, Germany
    Int J Clin Oncol 7:145-51. 2002
    The aim of this study was to improve the diagnostic efficiency of tumor markers in the diagnosis of lung cancer, by the mathematical evaluation of a tumor marker profile employing fuzzy logic modelling.
  33. ncbi Trabecular bone fracture healing simulation with finite element analysis and fuzzy logic
    Sandra J Shefelbine
    Institute for Orthopaedics and Biomechanics, Helmholtzstrasse 14, 89081 Ulm, Germany
    J Biomech 38:2440-50. 2005
    ..Using finite element analysis and the fuzzy logic for diaphyseal healing, the model simulated formation of woven bone in the fracture gap and subsequent ..
  34. ncbi Can fuzzy logic make things more clear?
    Jan A Hazelzet
    Pediatric ICU, Erasmus MC, Sophia, Rotterdam, The Netherlands
    Crit Care 13:116. 2009
    ..Clinical decision support and artificial intelligence using fuzzy logic and closed loop techniques are methods that might help us to handle this complexity in a safe, effective and ..
  35. ncbi Medical concepts related to individual risk are better explained with "plausibility" rather than "probability"
    Enzo Grossi
    Medical Department, Bracco SpA Milan, Italy
    BMC Cardiovasc Disord 5:31. 2005
    ..Few articles by the way have tried to focus the concept of "risk" at the individual subject level rather than at population level...
  36. ncbi Fuzzy logic and mechanical ventilation
    J H Bates
    Department of Medicine, Vermont Lung Center, The University of Vermont, Colchester Research Facility, Clochester, Vermont, USA
    Respir Care Clin N Am 7:363-77, vii. 2001
    ..When a patient is in respiratory failure, the effector's role is taken over by a mechanical ventilator. The issue that is considered in this article is how the physician might be taken out of the feedback loop...
  37. ncbi Evaluation of pulmonary function tests by using fuzzy logic theory
    Umit Uncü
    Programming Department, HASTEK Ltd Sti, Ankara, Turkey
    J Med Syst 34:241-50. 2010
    ..Fuzziness encountered during PFT is very important. In this study, the purpose is to use "fuzzy logic" approach to facilitate reliable and fast interpretation of PFT graphical outputs...
  38. ncbi Prediction of protein subcellular locations using fuzzy k-NN method
    Ying Huang
    State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Institute of Bioinformatics, Tsinghua University, Beijing 100084, People s Republic of China
    Bioinformatics 20:21-8. 2004
    ..Protein localization data are a valuable information resource helpful in elucidating protein functions. It is highly desirable to predict a protein's subcellular locations automatically from its sequence...
  39. ncbi Defining the expert ICU nurse
    Martin Christensen
    Bournemouth University, Nursing Studies, Bournemouth House, Christchurch Road, Bournemouth BH1 3LT, UK
    Intensive Crit Care Nurs 22:301-7. 2006
    ..The principles of abduction or fuzzy logic, derived from computer science, may be useful in assisting nurses to explain in terms, which others can ..
  40. ncbi A new approach to diabetic control: fuzzy logic and insulin pump technology
    Paul Grant
    Department of Medicine, Royal Sussex County Hospital, Eastern Road, Brighton, East Sussex, United Kingdom
    Med Eng Phys 29:824-7. 2007
    ..In this paper, we sought to explore the use of insulin pumps and the application of fuzzy logic technology to act as an 'artificial pancreas' in diabetic patients...
  41. ncbi FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis
    Lily R Liang
    Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA
    BMC Bioinformatics 7:S7. 2006
    ..Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention...
  42. ncbi Fuzzy cluster analysis of high-field functional MRI data
    Christian Windischberger
    NMR Group, Institute for Medical Physics, University of Vienna, , A-1090 Vienna, Austria
    Artif Intell Med 29:203-23. 2003
    ....
  43. ncbi Rule-base derivation for intensive care ventilator control using ANFIS
    H F Kwok
    Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK
    Artif Intell Med 29:185-201. 2003
    ..852, 0.962 and 0.787, respectively). The FAVeM's performance differed from the clinicians' performance (correlation coefficient of 0.332) but the resulting PaO(2) was still within safety limits...
  44. ncbi The "fuzzy logic" of the death-inducing signaling complex in lymphocytes
    Craig M Walsh
    Department of Molecular Biology and Biochemistry, University of California, Irvine, California 92697 3900, USA
    J Clin Immunol 23:333-53. 2003
    ..Rather than operating as a binary system, we propose that the DISCs formed around various DRs transduce signals leading to a variety of cellular fates...
  45. ncbi Improved sensitivity in the diagnosis of gastro-intestinal tumors by fuzzy logic-based tumor marker profiles including the tumor M2-PK
    Joachim Schneider
    Institut und Poliklinik für Arbeits und Sozialmedizin, Justus Liebig Universitat, Aulweg 129 111, D 35385 Giessen, Germany
    Anticancer Res 25:1507-15. 2005
    ..The aim of this study was to improve diagnostic efficiency in the detection of gastro-intestinal cancers by using fuzzy logic modeling in combination with a tumor marker panel (CEA, CA72-4, CA19-9) including Tumor M2-PK...
  46. ncbi Measurement of trabecular bone thickness in the limited resolution regime of in vivo MRI by fuzzy distance transform
    Punam K Saha
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Fourth Floor, Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 6021, USA
    IEEE Trans Med Imaging 23:53-62. 2004
    ..Finally, with in vivo micro-MR images from a prior study in rabbits subjected to corticosteroid exposure, it is demonstrated that short-term treatment resulting in trabecular thinning can be quantified with the new method...
  47. ncbi Controlling the false positive rate in fuzzy clustering using randomization: application to fMRI activation detection
    Hesamoddin Jahanian
    Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran
    Magn Reson Imaging 22:631-8. 2004
    ....
  48. ncbi Temporal representation and reasoning in medicine: Research directions and challenges
    Klaus Peter Adlassnig
    Section on Medical Expert and Knowledge Based Systems, Core Unit for Medical Statistics and Informatics, Medical University of Vienna, Spitalgasse 23, A 1090 Vienna, Austria
    Artif Intell Med 38:101-13. 2006
    ....
  49. ncbi Detecting subject-specific activations using fuzzy clustering
    Mohamed L Seghier
    Wellcome Trust Centre for Neuroimaging, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK
    Neuroimage 36:594-605. 2007
    ..The advantage of using FCP is that it searches all voxels systematically and can identify atypical activation patterns in a quantitative and unsupervised manner...
  50. ncbi Fully automatic segmentation of white matter hyperintensities in MR images of the elderly
    F Admiraal-Behloul
    Department of Radiology, C2S, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
    Neuroimage 28:607-17. 2005
    ....
  51. ncbi Gene networks reconstruction and time-series prediction from microarray data using recurrent neural fuzzy networks
    I A Maraziotis
    Department of Medical Physics, Medical School, University of Patras, Rio 26500, Greece
    IET Syst Biol 1:41-50. 2007
    ..The method surpasses other computational techniques, which have attempted genetic network reconstruction, by being able to recover significantly more biologically valid relationships among genes...
  52. ncbi Evaluation of an artificial intelligence guided inverse planning system: clinical case study
    Hui Yan
    Department of Radiation Oncology, Duke University Medical Center, Durham, NC 27710, USA
    Radiother Oncol 83:76-85. 2007
    ..For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared...
  53. ncbi A fuzzy logic based closed-loop control system for blood glucose level regulation in diabetics
    M S Ibbini
    Department of Electrical Engineering, Jordan University of Science and Technology, PO Box 3030, 22110 Irbid, Jordan
    J Med Eng Technol 29:64-9. 2005
    ..This control scheme is based on fuzzy logic control theory to maintain a normoglycaemic average of 4...
  54. ncbi Detecting clusters of different geometrical shapes in microarray gene expression data
    Dae-Won Kim
    Department of BioSystems and Advanced Information Technology Research Center, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon
    Bioinformatics 21:1927-34. 2005
    ..It is available from the authors upon request. SUPPLEMENTARY INFORMATION: Supplementary data are available at http://dragon.kaist.ac.kr/gk...
  55. ncbi An intelligent ventilation and oxygenation management system in neonatal intensive care using fuzzy trend template fitting
    Suliman Yousef Belal
    Institute of Science and Technology in Medicine, Keele University, Staffordshire, UK
    Physiol Meas 26:555-70. 2005
    ..The clinician agreed with the system ventilation decisions in 30 occasions (91%) and in 148 occasions for the system oxygenation decisions (94%). The overall percentage of the agreement between the system and the clinician was 93%...
  56. ncbi Evolving fuzzy rules to model gene expression
    Ricardo Linden
    FSMA RJ, R Monte Elíseo S N, CEP 27943 180, Macaé, RJ, Brazil
    Biosystems 88:76-91. 2007
    ..explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polish notation is used (RPN) to describe the rules and to facilitate the GP approach...
  57. ncbi Medical image analysis with fuzzy models
    J C Bezdek
    Department of Computer Science, University of West Florida, Pensacola 32514, USA
    Stat Methods Med Res 6:191-214. 1997
    ..We do not cover methods based on neural-like networks or fuzzy reasoning systems. These topics are covered in a recently published companion survey by keller et al...
  58. ncbi Morphology and morphometry of human chronic spinal cord injury using diffusion tensor imaging and fuzzy logic
    Benjamin M Ellingson
    Department of Biomedical Engineering, Marquette University, P O Box 1881, Milwaukee, WI 53201 1881, USA
    Ann Biomed Eng 36:224-36. 2008
    ..Apparent diffusion coefficients were measured and compared between subjects. A fuzzy logic tissue classification algorithm was used to segment gray and white matter regions for morphometric analysis, ..
  59. ncbi Increasing the efficiency of fuzzy logic-based gene expression data analysis
    Habtom Ressom
    Intelligent Systems Laboratory, Department of Electrical and Computer Engineering, University of Maine, Orono, Maine 04469, USA
    Physiol Genomics 13:107-17. 2003
    ..quot;Fuzzy logic" has been proposed as a method to analyze the relationships between genes and help decipher a genetic ..
  60. ncbi Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling
    Bree B Aldridge
    Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America
    PLoS Comput Biol 5:e1000340. 2009
    ..In this paper we apply a fuzzy logic framework to the analysis of a large, systematic dataset describing the dynamics of cell signaling downstream ..
  61. ncbi A novel approach to microcalcification detection using fuzzy logic technique
    H D Cheng
    Department of Computer Science, Utah State University, Logan 84322, USA
    IEEE Trans Med Imaging 17:442-50. 1998
    ..In this study, a novel approach to microcalcification detection based on fuzzy logic technique is presented. Microcalcifications are first enhanced based on their brightness and nonuniformity...
  62. ncbi Fuzzy C-means method for clustering microarray data
    Doulaye Dembele
    Institut de Genetique et de Biologie Moleculaire et Cellulaire, CNRS IMSERM ULP, BP 10142, 67404 Illkirch Cedex, France
    Bioinformatics 19:973-80. 2003
    ..However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes...
  63. ncbi Uncovering transcriptional interactions via an adaptive fuzzy logic approach
    Cheng Long Chuang
    Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
    BMC Bioinformatics 10:400. 2009
    ..This approach, combining an adaptive (learning) fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy...
  64. ncbi Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents
    Elif Derya Ubeyli
    Department of Electrical and Electronics Engineering, Faculty of Engineering, TOBB Ekonomi ve Teknoloji Universitesi, 06530 Sogutozu, Ankara, Turkey
    Comput Methods Programs Biomed 93:313-21. 2009
    ..The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach...
  65. ncbi Explicit logic circuits discriminate neural states
    Lane Yoder
    Department of Mathematics, University of Hawaii, Kapiolani, Honolulu, Hawaii, USA
    PLoS ONE 4:e4154. 2009
    ..The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems...
  66. ncbi A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data
    Mohamed N Ahmed
    Systems and Biomedical Engineering Department, Cairo University, Giza, Egypt
    IEEE Trans Med Imaging 21:193-9. 2002
    ..fuzzy segmentation of magnetic resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio-frequency coils or to problems ..
  67. ncbi Detection of epileptiform discharges in the EEG by a hybrid system comprising mimetic, self-organized artificial neural network, and fuzzy logic stages
    C J James
    Department of Electrical and Electronic Engineering, University of Canterbury, Christchurch, New Zealand
    Clin Neurophysiol 110:2049-63. 1999
    ..A multi-stage system for automated detection of epileptiform activity in the EEG has been developed and tested on pre-recorded data from 43 patients...
  68. ncbi Norepinephrine weaning in septic shock patients by closed loop control based on fuzzy logic
    Mehdi Merouani
    SAMU 93 EA 3409, Universite Paris 13, Hopital Avicenne, rue de Stalingrad, 93000 Bobigny, France
    Crit Care 12:R155. 2008
    ..We applied fuzzy logic principles to modify intravenous norepinephrine (noradrenaline) infusion rates during norepinephrine infusion ..
  69. ncbi Incorporating qualitative knowledge in enzyme kinetic models using fuzzy logic
    B Lee
    Department of Computer Science, Texas A and M University, College Station, USA
    Biotechnol Bioeng 62:722-9. 1999
    ..This strategy uses fuzzy logic-based factors to modify algebraic rate laws that account for partial kinetic characteristics...
  70. ncbi A recurrent fuzzy network for fuzzy temporal sequence processing and gesture recognition
    Chia-Feng Juang
    Department of Electrical Engineering, National Chung Hsing University, Taichung 402, Taiwan, ROC
    IEEE Trans Syst Man Cybern B Cybern 35:646-58. 2005
    ..In this paper, it has been applied on one-dimensional and two-dimensional fuzzy temporal sequence prediction and CCD-based temporal gesture recognition. The performance of FTRFN is verified from these examples...
  71. ncbi Genetically optimized fuzzy decision trees
    Witold Pedrycz
    IEEE Trans Syst Man Cybern B Cybern 35:633-41. 2005
    ..A series of experiments exploiting synthetic and machine learning data is used to illustrate the performance of the G-DTs...
  72. ncbi Missing value imputation improves clustering and interpretation of gene expression microarray data
    Johannes Tuikkala
    Department of Information Technology and TUCS, University of Turku, FI 20014 Turku, Finland
    BMC Bioinformatics 9:202. 2008
    ....
  73. ncbi Alpha-cut implemented fuzzy clustering algorithms and switching regressions
    Miin Shen Yang
    Department of Applied Mathematics, Chung Yuan Christian University, Taiwan, ROC
    IEEE Trans Syst Man Cybern B Cybern 38:588-603. 2008
    ..The proposed FCRalpha provides better results than FCR for environments with noise or outliers. Numerical examples show the robustness and the superiority of our proposed methods...
  74. ncbi Rough set based generalized fuzzy c-means algorithm and quantitative indices
    Pradipta Maji
    Center for Soft Computing Research, Indian Statistical Institute, Kolkata 700 108, India
    IEEE Trans Syst Man Cybern B Cybern 37:1529-40. 2007
    ..The effectiveness of the algorithm, along with a comparison with other algorithms, has been demonstrated both qualitatively and quantitatively on a set of real-life data sets...
  75. ncbi Single-trial lambda wave identification using a fuzzy inference system and predictive statistical diagnosis
    R Saatchi
    Computer Engineering and Digital Signal Processing, School of Engineering, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK
    J Neural Eng 1:21-31. 2004
    ..performance of a Bayesian approach called predictive statistical diagnosis (PSD) was compared with that of a fuzzy logic approach called a fuzzy inference system (FIS)...
  76. ncbi Segmentation of electron tomographic data sets using fuzzy set theory principles
    Edgar Garduno
    Depto Ciencias de la Computación, Instituto de Investigaciones en Matermáticas Aplicadas y en Sistemas, Universidad Nacional Autonoma de Mexico, Circuito Escolar s n, Cd Universitaria, C P 04510, Mexico City, Mexico
    J Struct Biol 162:368-79. 2008
    ..Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, ..
  77. ncbi [Noise image segmentation based on generalized fuzzy Gibbs random field]
    Jian Gong
    Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China
    Nan Fang Yi Ke Da Xue Xue Bao 26:390-3. 2006
    ..The optimal processing is executed through iterative conditional modes (ICM). The experiment results showed that the new approach could effectively segment the degenerated images...
  78. ncbi On the use of multi-objective evolutionary algorithms for the induction of fuzzy classification rule systems
    Christian Setzkorn
    Department of Computer Science, University of Liverpool, Prescot Street, Liverpool L7 8XP, UK
    Biosystems 81:101-12. 2005
    ..It is shown that the algorithm produces less complex classifiers that perform well on unseen data...
  79. ncbi Enhanced FMAM based on empirical kernel map
    Min Wang
    Department of Computer Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
    IEEE Trans Neural Netw 16:557-64. 2005
    ....
  80. ncbi Genetic-based fuzzy image filter and its application to image processing
    Chang Shing Lee
    Department of Information Management, Chang Jung Christian University, Tainan 711, Taiwan, ROC
    IEEE Trans Syst Man Cybern B Cybern 35:694-711. 2005
    ..On the subjective evaluation of those filtered images, GFIF also results in a higher quality of global restoration...
  81. ncbi A fuzzy reinforcement learning approach to power control in wireless transmitters
    David Vengerov
    Sun Microsystems Laboratories, Sunnyvale, CA 94086, USA
    IEEE Trans Syst Man Cybern B Cybern 35:768-78. 2005
    ..Such a large improvement is explained by the fact that ACFRL-2 allows transmitters to learn implicit coordination policies, which back off under stressful channel conditions as opposed to engaging in escalating "power wars."..
  82. ncbi Method to correct intensity inhomogeneity in MR images for atherosclerosis characterization
    Olivier Salvado
    Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44122, USA
    IEEE Trans Med Imaging 25:539-52. 2006
    ..In conclusion, we believe that the correction method shows promise for aiding human and computerized tissue classification from MR signal intensities...
  83. ncbi Fuzzy support vector machines for adaptive Morse code recognition
    Cheng Hong Yang
    Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan
    Med Eng Phys 28:925-31. 2006
    ..Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature...
  84. ncbi A support vector machine using the lazy learning approach for multi-class classification
    E Comak
    Department of Computer Engineering, Engineering and Architecture Faculty, Selcuk University, Konya, Turkey
    J Med Eng Technol 30:73-7. 2006
    ..Therefore, it is an alternative technique to fuzzy inference systems. Our studies show that LS-SVMs with the lazy learning approach can give comparable results to fuzzy LS-SVMs for multi-class classification...
  85. ncbi Feature-guided clustering of multi-dimensional flow cytometry datasets
    Qing T Zeng
    Decision Systems Group, Brigham and Women s Hospital, 310 Thorn Building, 75 Francis Street, Harvard Medical School, Boston, MA 02115, USA
    J Biomed Inform 40:325-31. 2007
    ....
  86. ncbi Deterministic approach to robust adaptive learning of fuzzy models
    Mohit Kumar
    Institute of Occupational and Social Medicine, Faculty of Medicine, University of Rostock, Germany
    IEEE Trans Syst Man Cybern B Cybern 36:767-80. 2006
    ..The proposed robust approach to the adaptive learning of fuzzy models has been illustrated through the examples of adaptive system identification, time-series prediction, and estimation of an uncertain process...
  87. ncbi Neural approximation of open-loop feedback rate control in satellite networks
    Marco Baglietto
    Department of Communications, Computer, and Systems Science DIST, University of Genoa, Genoa 16145, Italy
    IEEE Trans Neural Netw 16:1195-211. 2005
    ..As is shown in the simulation results, we obtain near-optimal reallocation strategies with a small real time computational effort and avoid the suboptimal transient periods introduced by the IPA gradient descent algorithm...
  88. ncbi Fuzzy-based adaptive bandwidth control for loss guarantees
    Peerapon Siripongwutikorn
    University of Pittsburgh, PA 15260, USA
    IEEE Trans Neural Netw 16:1147-62. 2005
    ..We propose an ABC algorithm called augmented Fuzzy (A-Fuzzy) control, whereby fuzzy logic control is used to keep an average queue length at an appropriate target value, and the measured packet loss ..
  89. ncbi Takagi-Sugeno fuzzy-model-based fault detection for networked control systems with Markov delays
    Ying Zheng
    IEEE Trans Syst Man Cybern B Cybern 36:924-9. 2006
    ..An example of a two-link inverted pendulum is used to illustrate the utility and viability of the proposed approaches...
  90. ncbi Interval fuzzy modeling applied to Wiener models with uncertainties
    Igor Skrjanc
    IEEE Trans Syst Man Cybern B Cybern 35:1092-5. 2005
    ..The resulting model has the potential to be used in the areas of robust control and fault detection...
  91. ncbi Finite-dimensional constrained fuzzy control for a class of nonlinear distributed process systems
    Huai-Ning Wu
    IEEE Trans Syst Man Cybern B Cybern 37:1422-30. 2007
    ..Finally, the proposed design method is applied to the control of the temperature profile of a catalytic rod...
  92. ncbi A fuzzy-based approach to remove clock skew and reset from one-way delay measurement
    Yu Lin
    National Laboratory of Switching and Networking, Beijing University of Posts and Telecommunication BUPT, Beijing 100876, China
    IEEE Trans Neural Netw 16:1125-35. 2005
    ..Numerical experiments demonstrate that FOC is more accurate and robust than the existing techniques. FOCs computation complexity O(N) is similar to that of CHA and its computing time is much less than that of convex-hull technique...
  93. ncbi Combining genetic algorithms and Lyapunov-based adaptation for online design of fuzzy controllers
    Vincenzo Giordano
    Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, 70125 Bari, Italy
    IEEE Trans Syst Man Cybern B Cybern 36:1118-27. 2006
    ..The effectiveness of the proposed method is confirmed using both numerical simulations on a known case study and experiments on a nonlinear hardware benchmark...
  94. ncbi The fuzzy transformation and its applications in image processing
    Yao Nie
    Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA
    IEEE Trans Image Process 15:910-27. 2006
    ..The advantage of the fuzzy generalizations is illustrated in the applications of DCT coded image deblocking, impulse removal, and noisy image sharpening...
  95. ncbi Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems
    Mehmet Kaya
    Department of Computer Engineering, Firat University, 23119 Elazig, Turkey
    IEEE Trans Syst Man Cybern B Cybern 35:326-38. 2005
    ..Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning...
  96. ncbi Asymmetric subsethood-product fuzzy neural inference system (ASuPFuNIS)
    C Shunmuga Velayutham
    Department of Physics and Computer Science, Faculty of Science, Dayalbagh Educational Institute, Dayalbagh, Agra 282005 India
    IEEE Trans Neural Netw 16:160-74. 2005
    ....
  97. ncbi A similarity-based robust clustering method
    Miin Shen Yang
    Department of Applied Mathematics, Chung Yuan Christian University, Chung Li, Taiwan 32023, ROC
    IEEE Trans Pattern Anal Mach Intell 26:434-48. 2004
    ..The computational complexity of SCM is also analyzed. Some experimental results of comparing the proposed SCM with the existing methods show the superiority of the SCM method...
  98. ncbi Reliability analysis of microarray data using fuzzy c-means and normal mixture modeling based classification methods
    Musa H Asyali
    Department of Biostatistics, Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Center PO Box 3354, MBC 03, Riyadh 11211, Saudi Arabia
    Bioinformatics 21:644-9. 2005
    ..In this study, we applied fuzzy c-means (FCM) and normal mixture modeling (NMM) based classification methods to separate microarray data into reliable and unreliable signal intensity populations...
  99. ncbi CAD tool for burn diagnosis
    Begona Acha
    Area de Teoría de la Señal y Comunicaciones, Escuela Superior de Ingenieros, University of Seville, Camino de los Descubrimientos s n, 41092 Seville, Spain
    Inf Process Med Imaging 18:294-305. 2003
    ..Clinical effectiveness of the method was demonstrated on 62 clinical burn wound images obtained from digital colour photographs, yielding an average classification success rate of 82% compared to expert classified images...
  100. ncbi Optimizing fuzzy clinical decision support rules using genetic algorithms
    Michael Krajnak
    GE Healthcare Information Technology, Milwaukee, WI 53226. USA
    Conf Proc IEEE Eng Med Biol Soc 1:5173-6. 2006
    ..Compared to pre-optimization, the optimized fuzzy inference system increased ROC area from 0.68 to 0.77, which can be translated to an increase in specificity from 74% to 82%, at a fixed sensitivity of 58%..
  101. ncbi Extraction of fluorescent cell puncta by adaptive fuzzy segmentation
    Tuan D Pham
    School of Computing and Information Technology, Griffith University, Nathan Campus, Australia
    Bioinformatics 20:2189-96. 2004
    ..Existing image processing methods for extracting fluorescent cell puncta do not provide useful results and therefore, there is a need to develop some new approaches for dealing with such a task effectively...

Research Grants87

  1. A BREATH TEST FOR LUNG CANCER
    Michael Phillips; Fiscal Year: 2007
    ..In a study of 451 subjects, a two-minute breath test for VOC biomarkers of lung cancer combined with fuzzy logic analysis of data predicted all TNM stages of disease with 84.6% sensitivity, 80.0% specificity and 0...
  2. Multifunction Prosthesis Control using Implanted Sensors
    Richard Weir; Fiscal Year: 2007
    ..A definitive design is anticipated to be ready for final testing and tweaking by the middle of year 4. The final year will be spent conducting the final systems integration. ..
  3. PORTABLE DEFIBRILLATOR FUZZY-LOGIC-BASED BATTERY METER
    Pritpal Singh; Fiscal Year: 2003
    ..University are collaborating in the pioneering development of an innovative, powerful approach, based on fuzzy logic, to battery SOC and SOH determination that is reliable, accurate, and economical...
  4. Automatic Detection of Critical Dermoscopy Features for Melanoma Diagnosis
    William Stoecker; Fiscal Year: 2007
    ..of a probability density function to specify single and paired melanoma colors via cluster methods and fuzzy logic techniques 4) identifying critical structural features including brown globules, abrupt border cutoff, ..
  5. Detection of chewing and swallowing to estimate eating patterns and energy intake
    Edward Sazonov; Fiscal Year: 2006
    ..Modern methods of computational intelligence such as artificial neural networks and fuzzy logic will be used along with statistical methods to achieve the highest 'accuracy of pattern recognition...
  6. PHASE RESETTING AND SENSORY INHIBITION IN THE CNS
    Nashaat Boutros; Fiscal Year: 1999
    ..Utilizing a fuzzy logic technique (that was developed by this group) evoked potential data containing the P50 mid-latency auditory ..
  7. PHASE RESETTING AND SENSORY INHIBITION IN THE CNS
    Nashaat Boutros; Fiscal Year: 2005
    ..Finally, we will demonstrate that both processes are deficient in schizophrenia patients. Utilizing a fuzzy logic technique and a single trial analysis method (both developed by this group) evoked potential data containing ..
  8. BIOPHYSICAL STUDIES OF FOLDING MUTANTS OF STAPH NUCLEASE
    David Shortle; Fiscal Year: 1999
    ..in staph nuclease will be developed, refined, and tested by building upon the extensive mutant database already in hand and by employing mathematical techniques such as statistical factor analysis, neural networks and fuzzy logic.
  9. VOLATILE MARKERS OF ORAL MALODOR IN THE BREATH
    Michael Phillips; Fiscal Year: 2004
    ....
  10. VOLATILE MARKERS OF PULMONARY TUBERCULOSIS IN THE BREATH
    Michael Phillips; Fiscal Year: 2006
    ..1% sensitivity and 95.1% specificity. Fuzzy logic analysis of breath VOCs predicted active pulmonary tuberculosis infection with sensitivity = 100% and ..
  11. Ethnic Specific Midlife Women's Attitudes Toward Physical Activity
    Eun Ok Im; Fiscal Year: 2009
    ..S., by directing the development of physical activity promotion programs that can serve ethnic minority midlife women through the Internet. ..
  12. Ethnic Specific Midlife Women's Attitudes Toward Physical Activity
    Eun Ok Im; Fiscal Year: 2007
    ..S., by directing the development of physical activity promotion programs that can serve ethnic minority midlife women through the Internet. ..
  13. Cancer Pain Management-Decision Support Computer Program
    Eun Ok Im; Fiscal Year: 2007
    ..Using theoretical triangulation, a feminist approach and fuzzy logic will guide the research process...
  14. SYNTHESIS, ANALYSIS, AND PERCEPTION OF VISIBLE SPEECH
    DOMINIC MASSARO; Fiscal Year: 1993
    ....
  15. Ethnic Specific Midlife Women's Attitudes Toward Physical Activity
    Eun Ok Im; Fiscal Year: 2010
    ..S., by directing the development of physical activity promotion programs that can serve ethnic minority midlife women through the Internet. ..
  16. PERCEPTION OF VISIBLE AND BIMODAL SPEECH
    DOMINIC MASSARO; Fiscal Year: 2004
    ..abstract_text> ..
  17. A Treatment Decision Modeling and Optimizing Technology
    Hao Ying; Fiscal Year: 2005
    ..It can be used to objectively and quantitatively analyze and compare different treatment options and selections, either prospectively or retrospectively. ..
  18. A Multiethnic Internet Study on Menopausal Symptoms
    Eun Ok Im; Fiscal Year: 2007
    ....
  19. PERCEPTUAL PROCESSING AND RECOGNITION OF SPEECH
    DOMINIC MASSARO; Fiscal Year: 1990
    ....
  20. Make Better Choices (MBC) - Multiple Behavior Change in Diet and Activity
    Bonnie Spring; Fiscal Year: 2010
    ..The proposed trial tests whether Make Better Choices treatment improves diet and activity more than stress management does and whether it is better to add new lifestyle goals all at once or one after another. ..
  21. Make Better Choices (MBC) - Multiple Behavior Change in Diet and Activity
    Bonnie Spring; Fiscal Year: 2010
    ..The proposed trial tests whether Make Better Choices treatment improves diet and activity more than stress management does and whether it is better to add new lifestyle goals all at once or one after another. ..
  22. CARBOHYDRATE CRAVING: BEHAVIOR/PSYCHOBIOLOGICAL FEATURES
    Bonnie Spring; Fiscal Year: 2001
    ..Results will indicate whether CHO cravers show an increased family prevalence of diabetes and display evidence of insulin resistance and blunting of the expected rise in the tryptophan ratio and leptin concentration after CHO intake. ..
  23. FLUOXETINE AS A QUIT SMOKING AID FOR DEPRESSION PRONE
    Bonnie Spring; Fiscal Year: 2001
    ....
  24. Multiple Behavior Change in Diet and Activity
    Bonnie Spring; Fiscal Year: 2007
    ..Findings will help to fill an important gap in clinical knowledge about how to optimize healthy simultaneous change in diet and activity among adults. ..
  25. ACCISS: Activating Collaborative CIS Support Services
    Bonnie Spring; Fiscal Year: 2007
    ..The study examines the impact on medical follow-up and provider-patient communication. ..
  26. Decision-Assist and Closed-Loop Fluid Resuscitation of Burn-Injured Patients
    George Kramer; Fiscal Year: 2009
    ..Because the computer can monitor the patient on a minute-by- minute basis without error, there is less chance of complications due to under-resuscitation or fluid overload. ..