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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Dettagli Bibliografici
Pubblicato in:EBioMedicine
Autori principali: Tavolara, Thomas E., Niazi, M. Khalid Khan, Ginese, Melanie, Piedra-Mora, Cesar, Gatti, Daniel M., Beamer, Gillian, Gurcan, Metin N.
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2020
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Research Paper
Accesso online: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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