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Accelerating Parkinson’s Disease drug development with federated learning approaches

Lookup NU author(s): Professor Camille CarrollORCiD, Professor Lynn RochesterORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).

Abstract

© The Author(s) 2024.Parkinson’s Disease is a progressive neurodegenerative disorder afflicting almost 12 million people. Increased understanding of its complex and heterogenous disease pathology, etiology and symptom manifestations has resulted in the need to design, capture and interrogate substantial clinical datasets. Herein we advocate how advances in the deployment of artificial intelligence models for Federated Data Analysis and Federated Learning can help spearhead coordinated and sustainable approaches to address this grand challenge.

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Author(s): Khanna A, Adams J, Antoniades C, Bloem BR, Carroll C, Cedarbaum J, Cosman J, Dexter DT, Dockendorf MF, Edgerton J, Gaetano L, Goikoetxea E, Hill D, Horak F, Izmailova ES, Kangarloo T, Katabi D, Kopil C, Lindemann M, Mammen J, Marek K, McFarthing K, Mirelman A, Muller M, Pagano G, Peterschmitt MJ, Ren J, Rochester L, Sardar S, Siderowf A, Simuni T, Stephenson D, Swanson-Fischer C, Wagner JA, Jones GB

Publication type: Article

Publication status: Published

Journal: npj Parkinson's Disease

Year: 2024

Volume: 10

Issue: 1

Online publication date: 21/11/2024

Acceptance date: 07/11/2024

Date deposited: 05/12/2024

ISSN (electronic): 2373-8057

Publisher: Nature Research

URL: https://doi.org/10.1038/s41531-024-00837-5

DOI: 10.1038/s41531-024-00837-5

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