Khanna, Amit;
Adams, Jamie;
Antoniades, Chrystalina;
Bloem, Bastiaan R;
Carroll, Camille;
Cedarbaum, Jesse;
Cosman, Joshua;
... Jones, Graham B; + view all
(2024)
Accelerating Parkinson’s Disease drug development with federated learning approaches.
npj Parkinson's Disease
, 10
, Article 225. 10.1038/s41531-024-00837-5.
Preview |
Text
federated learning 41531_2024_Article_837.pdf - Published Version Download (939kB) | Preview |
Abstract
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.
| Type: | Article |
|---|---|
| Title: | Accelerating Parkinson’s Disease drug development with federated learning approaches |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41531-024-00837-5 |
| Publisher version: | https://doi.org/10.1038/s41531-024-00837-5 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10213324 |
Archive Staff Only
 |
View Item |
