Affiliation: Mayo Clinic
- A 2012 Workshop: Vaccine and Drug Ontology in the Study of Mechanism and Effect (VDOSME 2012)Yongqun He
Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, and Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
J Biomed Semantics 3:12. 2012....
- A semantic-web oriented representation of the clinical element model for secondary use of electronic health records dataCui Tao
Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
J Am Med Inform Assoc 20:554-62. 2013..A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data...
- Terminology representation guidelines for biomedical ontologies in the semantic web notationsCui Tao
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States
J Biomed Inform 46:128-38. 2013..formal ontologies. We then evaluate the guidelines with a spectrum of widely used terminologies and ontologies to examine how the lexical guidelines are implemented, and whether our proposed guidelines would enhance interoperability...
- Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysisCui Tao
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
J Biomed Semantics 3:13. 2012..abstract:..
- An OWL meta-ontology for representing the Clinical Element ModelCui Tao
Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
AMIA Annu Symp Proc 2011:1372-81. 2011..These OWL representation specifications have been reviewed by CEM experts to ensure they capture the intended meaning of the model faithfully...
- Harmonization and semantic annotation of data dictionaries from the Pharmacogenomics Research Network: A case studyQian Zhu
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA Electronic address
J Biomed Inform 46:286-93. 2013..This represents a critical first step toward identifying and creating data standards for pharmacogenomics studies...
- Semantator: Semantic annotator for converting biomedical text to linked dataCui Tao
School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, United States Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, United States Electronic address
J Biomed Inform 46:882-93. 2013....
- A high throughput semantic concept frequency based approach for patient identification: a case study using type 2 diabetes mellitus clinical notesWei Qi Wei
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
AMIA Annu Symp Proc 2010:857-61. 2010..Current research on high throughput identification of patients with a specific phenotype is in its infancy. There is an urgent need to develop a general automatic approach for patient identification...
- Towards Semantic-Web Based Representation and Harmonization of Standard Meta-data Models for Clinical StudiesCui Tao
Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN
AMIA Summits Transl Sci Proc 2011:59-63. 2011..We consider such a harmonization would provide computable semantics of the models, thus facilitate the model reuse, model harmonization and data integration.1...
- Unified Medical Language System term occurrences in clinical notes: a large-scale corpus analysisStephen T Wu
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA
J Am Med Inform Assoc 19:e149-56. 2012..To characterise empirical instances of Unified Medical Language System (UMLS) Metathesaurus term strings in a large clinical corpus, and to illustrate what types of term characteristics are generalisable across data sources...
- Comprehensive temporal information detection from clinical text: medical events, time, and TLINK identificationSunghwan Sohn
Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
J Am Med Inform Assoc 20:836-42. 2013..Temporal information detection systems have been developed by the Mayo Clinic for the 2012 i2b2 Natural Language Processing Challenge...
- Application of a temporal reasoning framework tool in analysis of medical device adverse eventsKimberly K Clark
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
AMIA Annu Symp Proc 2011:1366-71. 2011..This results in an overall accuracy of 89%. This system should be pursued further to continue assessing its potential benefits in temporal analysis of medical device adverse events...
- Time-related patient data retrieval for the case studies from the pharmacogenomics research networkQian Zhu
Mayo Clinic, Rochester, MN, USA
J Med Syst 36:S37-42. 2012..The SPARQL query builder has been evaluated with a simulated EHR triple store to ensure its functionalities...
- CNTRO 2.0: A Harmonized Semantic Web Ontology for Temporal Relation Inferencing in Clinical NarrativesCui Tao
Mayo Clinic College of Medicine, Rochester, MN
AMIA Summits Transl Sci Proc 2011:64-8. 2011..This paper introduces CNTRO 2.0, which tries to harmonize CNTRO 1.0 and a list of existing time ontologies or top-level ontologies into a unified model-an OWL based ontology of temporal relations for clinical research...
- CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical NarrativesCui Tao
Mayo Clinic College of Medicine, Rochester, MN
AMIA Annu Symp Proc 2010:787-91. 2010..More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully...
- Semantator: annotating clinical narratives with semantic web ontologiesDezhao Song
Division of Biomedical Statistics and Informatics, Mayo Clinic 200 First Street SW, Rochester, MN 55905
AMIA Summits Transl Sci Proc 2012:20-9. 2012..We present discussions based on user experiences of using Semantator...