Article

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young

2024-01-23

Abstract excerpt

<h4>Background</h4> Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. <h4>Methods</h4> We compared three approaches for developing c...

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Literature Corpus work: a83e9a10-bbe2-5112-a0ad-3801c4a9d1b7
DOI: 10.1101/2024.01.22.24301429

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Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the YoungDOI 10.1101/2024.01.22.24301429Read

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