Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials

Journal of Cardiovascular Translational Research

Volumn 10, Issue 3, 2017, Pages 313-321

  Jonnalagadda, Siddhartha R ^a,b   Adupa, Abhishek K ^a   Garg, Ravi P ^a   Corona Cox, Jessica ^a   Shah, Sanjiv J ^a  

^a NORTHWESTERN UNIVERSITY   (United States)

^b MICROSOFT   (United States)

Author keywords

Clinical trials; Information extraction; Natural language processing; Precision medicine

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATION; CLINICAL STUDY; CLINICAL TRIAL (TOPIC); DATA MINING; ELECTRONIC HEALTH RECORD; HEART FAILURE WITH PRESERVED EJECTION FRACTION; HUMAN; INFORMATION PROCESSING; MAJOR CLINICAL STUDY; MEDICAL INFORMATION; PATIENT IDENTIFICATION; PERSONALIZED MEDICINE; PREDICTIVE VALUE; PRIORITY JOURNAL; SENSITIVITY ANALYSIS; CLASSIFICATION; ECHOCARDIOGRAPHY; HEART FAILURE; HEART STROKE VOLUME; NATURAL LANGUAGE PROCESSING; ORGANIZATION AND MANAGEMENT; PATHOPHYSIOLOGY; PATIENT SELECTION; PHENOTYPE; PROCEDURES; REPRODUCIBILITY;

ALGORITHMS; CLINICAL TRIALS AS TOPIC; DATA MINING; ECHOCARDIOGRAPHY; ELECTRONIC HEALTH RECORDS; ELIGIBILITY DETERMINATION; HEART FAILURE; HUMANS; NATURAL LANGUAGE PROCESSING; PATIENT SELECTION; PHENOTYPE; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; STROKE VOLUME;

EID: 85020169156     PISSN: 19375387     EISSN: 19375395     Source Type: Journal    
DOI: 10.1007/s12265-017-9752-2     Document Type: Article

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