Extracting information from the text of electronic medical records to improve case detection: A systematic review

Journal of the American Medical Informatics Association

Volumn 23, Issue 5, 2016, Pages 1007-1015

  Ford, Elizabeth ^a   Carroll, John A ^b   Smith, Helen E ^a   Scott, Donia ^b   Cassell, Jackie A ^a  

^a BRIGHTON AND SUSSEX MEDICAL SCHOOL   (United Kingdom)

^b UNIVERSITY OF SUSSEX   (United Kingdom)

Author keywords

Case detection; Data quality; Electronic health records; Review; Text mining

Indexed keywords

DIAGNOSTIC TEST ACCURACY STUDY; DOCTOR PATIENT RELATION; ELECTRONIC HEALTH RECORD; ELECTRONIC MEDICAL RECORD; HUMAN; MACHINE LEARNING; MINING; PREDICTIVE VALUE; RECALL; RECEIVER OPERATING CHARACTERISTIC; SYSTEMATIC REVIEW; ALGORITHM; DATA MINING; DIAGNOSIS; INFORMATION RETRIEVAL; NATURAL LANGUAGE PROCESSING; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; DATA MINING; DIAGNOSIS; ELECTRONIC HEALTH RECORDS; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MACHINE LEARNING; NATURAL LANGUAGE PROCESSING; SENSITIVITY AND SPECIFICITY;

EID: 84995810431     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocv180     Document Type: Article

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