Can PRISM predict length of PICU stay? An analysis of 2000 cases

Medical Informatics and the Internet in Medicine

Volumn 28, Issue 3, 2003, Pages 209-219

  Michel, Erik ^a,c   Zernikow, Boris ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b UNIVERSITY OF WITTEN HERDECKE   (Germany)

^c NONE   (Germany)

Author keywords

Disease severity; Length of stay; Neural network; Paediatric intensive care; PRISM

Indexed keywords

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHILD; COMPUTER ANALYSIS; CORRELATION COEFFICIENT; DATA ANALYSIS; DISEASE SEVERITY; HEALTH CARE QUALITY; HOSPITAL ADMISSION; HUMAN; INFANT; INTENSIVE CARE; LENGTH OF STAY; LINEAR SYSTEM; NEWBORN; NONLINEAR SYSTEM; RETROSPECTIVE STUDY; SCORING SYSTEM;

COHORT STUDIES; HEALTH SERVICES RESEARCH; HUMANS; INTENSIVE CARE UNITS, PEDIATRIC; LENGTH OF STAY; NETHERLANDS; NEURAL NETWORKS (COMPUTER); PATIENT READMISSION; PROBABILITY; RETROSPECTIVE STUDIES; SEVERITY OF ILLNESS INDEX;

EID: 84860417248     PISSN: 14639238     EISSN: None     Source Type: Journal    
DOI: 10.1080/14639230310001617814     Document Type: Article

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