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Multi-modality machine learning predicting Parkinson’s disease

Abstract Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson’s disease (PD) risk and systematically dev...

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Hlavní autoři: Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, Lana Sargent, Anant Dadu, Ivo Violich, Elizabeth Hutchins, David Saffo, Sara Bandres-Ciga, Jonggeol Jeff Kim, Yeajin Song, Melina Maleknia, Matt Bookman, Willy Nojopranoto, Roy H. Campbell, Sayed Hadi Hashemi, Juan A. Botia, John F. Carter, David W. Craig, Kendall Van Keuren-Jensen, Huw R. Morris, John A. Hardy, Cornelis Blauwendraat, Andrew B. Singleton, Faraz Faghri, Mike A. Nalls
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2022-04-01
Edice:npj Parkinson's Disease
On-line přístup:https://doi.org/10.1038/s41531-022-00288-w
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