Automated Detection of Postoperative Surgical Site Infections Using Supervised Methods with Electronic Health Record Data

Studies in Health Technology and Informatics

Volumn 216, Issue , 2015, Pages 706-710

  Hu, Zhen ^a   Simon, Gyorgy J ^a   Arsoniadis, Elliot G ^a,b   Wang, Yan ^a   Kwaan, Mary R ^b   Melton, Genevieve B ^a,b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b UNIVERSITY OF MINNESOTA MEDICAL SCHOOL   (United States)

Author keywords

Electronic Health Records; National Surgical Quality Improvement Project; Supervised Learning; Surgical Site Infection

Indexed keywords

BIOINFORMATICS; EHEALTH; RECORDS MANAGEMENT; SUPERVISED LEARNING;

AUTOMATED DETECTION; CONSTRUCTION PROCESS; ELECTRONIC HEALTH RECORD; NEGATIVE PREDICTIVE VALUE; PROTOTYPE SYSTEM; QUALITY IMPROVEMENT; SUPERVISED METHODS; SURGICAL SITE INFECTIONS;

TRANSPLANTATION (SURGICAL);

CLINICAL DECISION SUPPORT SYSTEM; COMPUTER ASSISTED DIAGNOSIS; DATA MINING; ELECTRONIC HEALTH RECORD; HUMAN; ORGANIZATION AND MANAGEMENT; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICS AND NUMERICAL DATA; SUPERVISED MACHINE LEARNING; SURGICAL WOUND INFECTION;

DATA MINING; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSIS, COMPUTER-ASSISTED; ELECTRONIC HEALTH RECORDS; HUMANS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPERVISED MACHINE LEARNING; SURGICAL WOUND INFECTION;

EID: 84951932330     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-61499-564-7-706     Document Type: Conference Paper

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