Development and performance of text-mining algorithms to extract socioeconomic status from de-identified electronic health records

Pacific Symposium on Biocomputing

Volumn 0, Issue , 2017, Pages 230-241

  Hollister, Brittany M ^a   Restrepo, Nicole A ^b   Farber Eger, Eric ^c   Crawford, Dana C ^b   Aldrich, Melinda C ^c   Non, Amy ^d  

^a VANDERBILT UNIVERSITY   (United States)

^b CASE WESTERN RESERVE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; EMPLOYMENT; HEALTH; RECORDS MANAGEMENT; RISK ASSESSMENT;

BIOBANKS; ELECTRONIC HEALTH; GENETIC STUDIES; HEALTH RECORDS; KEY FACTORS; MINING ALGORITHMS; PERFORMANCE; SOCIO-ECONOMIC STATUS; STATUS INFORMATIONS; TEXT-MINING;

POPULATION STATISTICS;

ALGORITHM; BIOLOGY; DATA MINING; ELECTRONIC HEALTH RECORD; EVALUATION STUDY; FEMALE; HEALTH STATUS; HUMAN; MALE; PROCEDURES; SOCIAL CLASS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATA MINING; ELECTRONIC HEALTH RECORDS; FEMALE; HEALTH STATUS; HUMANS; MALE; SOCIAL CLASS;

EID: 85021859717     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: 10.1142/9789813207813_0023     Document Type: Conference Paper

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