Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning

BACKGROUND: Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that effectively address its heterogeneity. To meet these shortcomings, we show that Diversity Outbred (DO) mice reflect human-like genetic div...

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Detalles Bibliográficos
Publicado en:EBioMedicine
Main Authors: Tavolara, Thomas E., Niazi, M. Khalid Khan, Ginese, Melanie, Piedra-Mora, Cesar, Gatti, Daniel M., Beamer, Gillian, Gurcan, Metin N.
Formato: Artigo
Idioma:Inglês
Publicado: Elsevier 2020
Assuntos:
Research Paper
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC7658666/
https://ncbi.nlm.nih.gov/pubmed/33166789
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ebiom.2020.103094
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