Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

Abstract Digital measures of health status captured during daily life could greatly augment current in-clinic assessments for rheumatoid arthritis (RA), to enable better assessment of disease progression and impact. This work presents results from weaRAble-PRO, a 14-day observational study, which ai...

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Bibliographic Details
Main Authors: Andrew P. Creagh, Valentin Hamy, Hang Yuan, Gert Mertes, Ryan Tomlinson, Wen-Hung Chen, Rachel Williams, Christopher Llop, Christopher Yee, Mei Sheng Duh, Aiden Doherty, Luis Garcia-Gancedo, David A. Clifton
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-024-01013-y

Internet

https://doi.org/10.1038/s41746-024-01013-y

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