PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT

Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthcare delivery in the United States. Patient readmiss...

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Pubblicato in:Pac Symp Biocomput
Autori principali: SHAMEER, KHADER, JOHNSON, KIPP W, YAHI, ALEXANDRE, MIOTTO, RICCARDO, LI, LI, RICKS, DORAN, JEBAKARAN, JEBAKUMAR, KOVATCH, PATRICIA, SENGUPTA, PARTHO P., GELIJNS, ANNETINE, MOSKOVITZ, ALAN, DARROW, BRUCE, REICH, DAVID L, KASARSKIS, ANDREW, TATONETTI, NICHOLAS P., PINNEY, SEAN, DUDLEY, JOEL T
Natura: Artigo
Lingua:Inglês
Pubblicazione: 2016
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Article
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC5362124/
https://ncbi.nlm.nih.gov/pubmed/27896982
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