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Article

Learning to predict post-hospitalization VTE risk from EHR data.

AMIA ... Annual Symposium proceedings. AMIA Symposium - 1 Jan 2012

Kawaler Emily, Cobian Alexander, Peissig Peggy, Cross Deanna, Yale Steve, Craven Mark

Abstract excerpt

We consider the task of predicting which patients are most at risk for post-hospitalization venothromboembolism (VTE) using information automatically elicited from an EHR. Given a set of cases and controls, we use machine-learning methods to induce models for making these predictions. Our empirical evaluation of this approach offers a number of interesting and important conclusions. We identify several risk...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 23304314
PMCID: PMC3540493

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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