Using EHRs and Machine Learning for Heart Failure Survival Analysis

Studies in Health Technology and Informatics

Volumn 216, Issue , 2015, Pages 40-44

  Panahiazar, Maryam ^a   Taslimitehrani, Vahid ^b   Pereira, Naveen ^a   Pathak, Jyotishman ^a  

^a MAYO CLINIC   (United States)

^b Wright State University   (United States)

Author keywords

Electronic Health Records; Heart Failure; Machine Learning; Survival Score

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; CARDIOLOGY; DIAGNOSIS; DISEASES; EHEALTH; HEART; LEARNING SYSTEMS; PATIENT TREATMENT; RECORDS MANAGEMENT; RISK ASSESSMENT;

ELECTRONIC HEALTH RECORD; ELECTRONIC HEALTH RECORD (EHRS); HEART FAILURE; HIGH-RISK PATIENTS; RISK PREDICTION MODELS; SURVIVAL ANALYSIS; SURVIVAL SCORE; THERAPEUTIC INTERVENTION;

HEALTH RISKS;

AGED; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; DATA MINING; DEATH, SUDDEN, CARDIAC; ELECTRONIC MEDICAL RECORD; FEMALE; HEALTH SURVEY; HEART FAILURE; HUMAN; MACHINE LEARNING; MALE; MORTALITY; NATURAL LANGUAGE PROCESSING; PREVALENCE; PROCEDURES; RISK FACTOR; STATISTICS AND NUMERICAL DATA; SURVIVAL; UNITED STATES;

AGED; DATA MINING; DEATH, SUDDEN, CARDIAC; ELECTRONIC HEALTH RECORDS; FEMALE; HEART FAILURE; HUMANS; MACHINE LEARNING; MALE; MINNESOTA; NATURAL LANGUAGE PROCESSING; PATTERN RECOGNITION, AUTOMATED; POPULATION SURVEILLANCE; PREVALENCE; RISK FACTORS; SURVIVAL ANALYSIS;

EID: 84952006219     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-61499-564-7-40     Document Type: Conference Paper

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