Exploring Joint AB-LSTM with Embedded Lemmas for Adverse Drug Reaction Discovery

IEEE Journal of Biomedical and Health Informatics

Volumn 23, Issue 5, 2019, Pages 2148-2155

  Santiso, Sara ^a   Pérez, Alicia ^a   Casillas, Arantza ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY   (Spain)

Author keywords

Adverse drug reactions; deep neural networks; electronic health records

Indexed keywords

DEEP NEURAL NETWORKS; HEALTH; PHARMACODYNAMICS; RECORDS MANAGEMENT; TEXT MINING;

ADVERSE DRUG REACTION (ADRS); ADVERSE DRUG REACTIONS; ELECTRONIC HEALTH RECORD; ELECTRONIC HEALTH RECORD (EHRS); EVENT EXTRACTION; SHORT TERM MEMORY; SKEWED CLASS DISTRIBUTIONS; WORLD HEALTH ORGANIZATION;

LONG SHORT-TERM MEMORY;

ADVERSE DRUG REACTION; ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; DEEP NEURAL NETWORK; ELECTRONIC HEALTH RECORD; ENTROPY; LONG SHORT TERM MEMORY NETWORK; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MEMORY CELL; PATIENT SAFETY; PHARMACOVIGILANCE; PRINCIPAL COMPONENT ANALYSIS; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SHORT TERM MEMORY; SOFTWARE VALIDATION; THEORETICAL MODEL; THEORY VALIDATION; TRAINING; WORKLOAD; WORLD HEALTH ORGANIZATION; CLASSIFICATION; DATA MINING; HUMAN; MEDICAL INFORMATICS; PROCEDURES;

ALGORITHMS; DATA MINING; DEEP LEARNING; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; ELECTRONIC HEALTH RECORDS; HUMANS; MEDICAL INFORMATICS;

EID: 85056203488     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2018.2879744     Document Type: Article

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