2012 - Member of the National Academy of Medicine (NAM)
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Health informatics, Information retrieval and Data science. His Artificial intelligence study combines topics from a wide range of disciplines, such as Event, Predictive value, Event reporting and Confidence interval. His Natural language processing research is multidisciplinary, incorporating elements of Event type, Clinical information and Coding.
His Health informatics study combines topics in areas such as Decision support system, Clinical trial, Cohort and Knowledge management. His Information retrieval research includes themes of Gold standard, Data warehouse, Completeness and MEDLINE. His studies deal with areas such as Domain, Health Administration Informatics, World Wide Web and Observational Studies as Topic as well as Data science.
George Hripcsak mainly investigates Artificial intelligence, Observational study, Data science, Natural language processing and MEDLINE. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Vocabulary, Data mining and Process. George Hripcsak performs integrative Observational study and Informatics research in his work.
His Natural language processing research is multidisciplinary, incorporating perspectives in Terminology and Information retrieval.
Observational study, Internal medicine, Cohort study, MEDLINE and Cohort are his primary areas of study. George Hripcsak combines subjects such as Machine learning, Scale, Database and Artificial intelligence with his study of Observational study. His work deals with themes such as Vocabulary, Set and Natural language processing, which intersect with Artificial intelligence.
His Cohort study study incorporates themes from Kidney disease, Hydroxychloroquine, Adverse effect, Rheumatoid arthritis and Veterans Affairs. The MEDLINE study combines topics in areas such as Electronic health record, Coronavirus disease 2019, Emergency medicine and Comorbidity. George Hripcsak has researched Cohort in several fields, including Odds ratio, Breast cancer and Retrospective cohort study.
His primary areas of study are Observational study, Internal medicine, Cohort study, MEDLINE and Hazard ratio. His studies in Observational study integrate themes in fields like Machine learning, Database, Healthcare Cost and Utilization Project, Artificial intelligence and Data quality. The study incorporates disciplines such as Consistency, Reliability and Process in addition to Artificial intelligence.
His biological study spans a wide range of topics, including Hydroxychloroquine, Adverse effect, Retrospective cohort study, Rheumatoid arthritis and Veterans Affairs. George Hripcsak has included themes like SNOMED CT, Source data, Natural language processing, Emergency medicine and Coronavirus disease 2019 in his MEDLINE study. His Data science research integrates issues from Precision medicine, Health informatics and Data sharing.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19.
Joshua Geleris;Yifei Sun;Jonathan Platt;Jason Zucker.
The New England Journal of Medicine (2020)
Agreement, the F-Measure, and Reliability in Information Retrieval
George Hripcsak;Adam S. Rothschild.
Journal of the American Medical Informatics Association (2005)
Next-generation phenotyping of electronic health records
George Hripcsak;David J Albers.
Journal of the American Medical Informatics Association (2013)
Detecting adverse events using information technology.
David W. Bates;R. Scott Evans;Harvey J. Murff;Peter D. Stetson.
Journal of the American Medical Informatics Association (2003)
Automated encoding of clinical documents based on natural language processing.
Carol Friedman;Lyudmila Shagina;Yves A. Lussier;George Hripcsak.
Journal of the American Medical Informatics Association (2004)
Design lessons from the fastest q&a site in the west
Lena Mamykina;Bella Manoim;Manas Mittal;George Hripcsak.
human factors in computing systems (2011)
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers
George Hripcsak;Jon D. Duke;Nigam H. Shah;Christian G. Reich.
Studies in health technology and informatics (2015)
Knowledge-based approaches to the maintenance of a large controlled medical terminology.
James J. Cimino;Paul D. Clayton;George Hripcsak;Stephen B. Johnson.
Journal of the American Medical Informatics Association (1994)
Unlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing
George Hripcsak;Carol Friedman;Philip O. Alderson;William DuMouchel.
Annals of Internal Medicine (1995)
Caveats for the use of operational electronic health record data in comparative effectiveness research.
William R. Hersh;Mark G. Weiner;Peter J. Embi;Judith R. Logan.
Medical Care (2013)
Profile was last updated on December 6th, 2021.
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