Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 1721-1730

  Caruana, Rich ^a   Lou, Yin ^b   Gehrke, Johannes ^c   Koch, Paul ^a   Sturm, Marc ^d   Elhadad, Noémie ^e  

^a MICROSOFT RESEARCH   (United States)

^b LINKEDIN CORPORATION   (United States)

^c MICROSOFT   (United States)

^d NEW YORK PRESBYTERIAN HOSPITAL   (United States)

^e Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Additive models; Classification; Healthcare; Intelligibility; Interaction detection; Logistic regression; Risk prediction

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DATA MINING; DECISION TREES; FORECASTING; FORESTRY; HOSPITALS; LEARNING SYSTEMS; REGRESSION ANALYSIS; SPEECH INTELLIGIBILITY;

ADDITIVE MODELS; GENERALIZED ADDITIVE MODEL; INTERACTION DETECTION; LOGISTIC REGRESSIONS; MACHINE LEARNING METHODS; MISSION CRITICAL APPLICATIONS; PAIRWISE INTERACTION; RISK PREDICTIONS;

HEALTH CARE;

EID: 84954180053     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2788613     Document Type: Conference Paper

References (7)

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