A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support

BACKGROUND: Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood...

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Detalles Bibliográficos
Autores principales: Connolly, Brian, Cohen, K. Bretonnel, Santel, Daniel, Bayram, Ulya, Pestian, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545857/
https://www.ncbi.nlm.nih.gov/pubmed/28784111
http://dx.doi.org/10.1186/s12859-017-1736-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545857/
https://www.ncbi.nlm.nih.gov/pubmed/28784111
http://dx.doi.org/10.1186/s12859-017-1736-3

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