Detecting the impact of subject characteristics on machine learning-based diagnostic applications

Collection of high-dimensional, longitudinal digital health data has the potential to support a wide-variety of research and clinical applications including diagnostics and longitudinal health tracking. Algorithms that process these data and inform digital diagnostics are typically developed using t...

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Detalles Bibliográficos
Autores principales: Chaibub Neto, Elias, Pratap, Abhishek, Perumal, Thanneer M., Tummalacherla, Meghasyam, Snyder, Phil, Bot, Brian M., Trister, Andrew D., Friend, Stephen H., Mangravite, Lara, Omberg, Larsson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789029/
https://www.ncbi.nlm.nih.gov/pubmed/31633058
http://dx.doi.org/10.1038/s41746-019-0178-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789029/
https://www.ncbi.nlm.nih.gov/pubmed/31633058
http://dx.doi.org/10.1038/s41746-019-0178-x

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