Carol Friedman focuses on Artificial intelligence, Natural language processing, Information retrieval, Domain and Pharmacovigilance. His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His Natural language processing research is multidisciplinary, incorporating perspectives in XML, Clinical information and Ambiguity.
Carol Friedman has included themes like Text mining and Text processing in his Information retrieval study. His work investigates the relationship between Domain and topics such as Controlled vocabulary that intersect with problems in Semantics. His Pharmacovigilance research incorporates elements of Data mining and Health records.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Information retrieval, Unified Medical Language System and Data science. His study in Artificial intelligence focuses on Information extraction in particular. His research in Natural language processing intersects with topics in Controlled vocabulary and Semantics.
His Information retrieval research includes elements of Annotation, Cluster analysis, Recall and Encoding. His Unified Medical Language System study combines topics from a wide range of disciplines, such as Abbreviations as Topic, Classifier, Ambiguity and Semantic network. His Data science research is multidisciplinary, relying on both Data mining and Pharmacovigilance.
Carol Friedman mostly deals with Artificial intelligence, Pharmacovigilance, Medical emergency, Intensive care medicine and Drug reaction. The various areas that Carol Friedman examines in his Artificial intelligence study include Regular expression, Biomedicine and Natural language processing. The various areas that Carol Friedman examines in his Natural language processing study include Mental health, Health informatics and Substance abuse.
His Pharmacovigilance research is multidisciplinary, incorporating elements of Drug development and Data mining. His study explores the link between Medical emergency and topics such as Point of care that cross with problems in Information retrieval and Evidence-based practice. His study on Intensive care medicine also encompasses disciplines like
Carol Friedman mainly focuses on Pharmacovigilance, Data mining, Internal medicine, Artificial intelligence and Drug development. His studies deal with areas such as Observational study, Electronic health record, Healthcare data, Data science and Receiver operating characteristic as well as Pharmacovigilance. In his research, Logistic regression, Confounding Factors and Clinical information is intimately related to Drug reaction, which falls under the overarching field of Data mining.
The Case-control study research Carol Friedman does as part of his general Internal medicine study is frequently linked to other disciplines of science, such as Metformin, therefore creating a link between diverse domains of science. Carol Friedman interconnects Biomedicine and Reading in the investigation of issues within Artificial intelligence. His Drug development research incorporates themes from Social media and Adverse effect, Adverse Event Reporting System.
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A General Natural-language Text Processor for Clinical Radiology
Carol Friedman;Philip O. Alderson;John H. M. Austin;James J. Cimino.
Journal of the American Medical Informatics Association (1994)
GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles.
Carol Friedman;Pauline Kra;Hong Yu;Michael Krauthammer.
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)
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)
System and method for language extraction and encoding utilizing the parsing of text data in accordance with domain parameters
Novel data-mining methodologies for adverse drug event discovery and analysis.
Rave Harpaz;William DuMouchel;William DuMouchel;Nigam H. Shah;David Madigan;David Madigan.
Clinical Pharmacology & Therapeutics (2012)
GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data
Andrey Rzhetsky;Ivan Iossifov;Tomohiro Koike;Michael Krauthammer.
Journal of Biomedical Informatics (2004)
Active Computerized Pharmacovigilance Using Natural Language Processing, Statistics, and Electronic Health Records: A Feasibility Study
Xiaoyan Wang;George Hripcsak;Marianthi Markatou;Carol Friedman.
Journal of the American Medical Informatics Association (2009)
Medical Language Processing: Computer Management of Narrative Data
Naomi. Sager;Carol Friedman;Margaret S. Lyman.
Using BLAST for identifying gene and protein names in journal articles.
Michael Krauthammer;Andrey Rzhetsky;Pavel Morozov;Carol Friedman;Carol Friedman.
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