Bayesian hierarchical rule modeling for predicting medical conditions

DOI10.1214/11-AOAS522zbMath1243.62036arXiv1206.6653OpenAlexW1985855931MaRDI QIDQ439156

Tyler H. McCormick, David Madigan, Cynthia Rudin

Publication date: 1 August 2012

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1206.6653

zbMATH Keywords

hierarchical modelmachine learningassociation rule mininghealthcare surveillance

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05) Medical applications (general) (92C50)

Related Items (6)

Interpretable classifiers using rules and Bayesian analysis: building a better stroke prediction model ⋮ Bayesian hierarchical rule modeling for predicting medical conditions ⋮ Learning customized and optimized lists of rules with mathematical programming ⋮ Sequential event prediction ⋮ Unnamed Item ⋮ Unnamed Item

Cites Work

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• Bayesian hierarchical rule modeling for predicting medical conditions
• Modeling item-item similarities for personalized recommendations on Yahoo! front page
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• The mixture transition distribution model for high-order Markov chains and non-Gaussian time series
• Sequential event prediction
• Model-Based Clustering, Discriminant Analysis, and Density Estimation

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