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

Authors:
Creagh AP; Hamy V; Yuan H; Mertes G; Tomlinson R and 8 more

Journal:
NPJ Digit Med

Publication Year: 2024

DOI:
10.1038/s41746-024-01013-y

PMCID:
PMC10861520

PMID:
38347090

Journal Information

Full Title: NPJ Digit Med

Abbreviation: NPJ Digit Med

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Health Care Sciences & Services

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
4/6
66.7% Transparent
Transparency Indicators
Click on green indicators to view evidence text
Core Indicators
Data Sharing
Evidence found in paper:

"our self-supervised learning activity prediction code and trained models are publicly available at: https://github com/oxwearables/ssl-wearables including pre-trained models on 100k participants in the uk biobank."

Evidence found in paper:

"Competing interests A.P.C, H.Y, G.M, A.D, D.A.C are employees of the University of Oxford. A.P.C is a GSK postdoctoral fellow and acknowledges the support of GSK. D.A.C received research funding from GSK to conduct this work. In addition, A.D., H.Y., and G.M. acknowledge the support of Novo Nordisk plc. A.D. AD is supported by the Wellcome Trust [223100/Z/21/Z]. V.H, W-H.C, R.T, R.W and L.G-G are employees of GSK and own stock and or shares. C.L, C.Y, M.S.D are employees of Analysis Group, which received research funding from GSK to conduct the study."

Evidence found in paper:

"We are grateful to all the study participants and their families for their time and dedication to this study. The authors would also like to thank Priyanka Bobbili PhD, Julien Bendelac BSc, Jessica Landry MSc, Maral DerSarkissian PhD, Mihran Yenikomshian MBA, and Med Kouaici (MEng) from Analysis Group (MA, USA) for their support in app. design & development and data collection, and to Elinor Mody from Reliant Medical Group (MA, USA) for patient recruitment. The weaRAble-PRO study was funded and sponsored by GSK Plc. The research described in this paper was funded by GSK Plc. This research also acknowledges support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). Aiden Doherty is supported by the Wellcome Trust [223100/Z/21/Z]. Competing interests: A.P.C, H.Y, G.M, A.D, D.A.C are employees of the University of Oxford. A.P.C is a GSK postdoctoral fellow and acknowledges the support of GSK. D.A.C received research funding from GSK to conduct this work. In addition, A.D., H.Y., and G.M. acknowledge the support of Novo Nordisk plc. A.D. AD is supported by the Wellcome Trust [223100/Z/21/Z]. V.H, W-H.C, R.T, R.W and L.G-G are employees of GSK and own stock and or shares. C.L, C.Y, M.S.D are employees of Analysis Group, which received research funding from GSK to conduct the study."

Protocol Registration
Open Access
Paper is freely available to read
Additional Indicators
Replication
Novelty Statement
Assessment Info

Tool: rtransparent

OST Version: N/A

Last Updated: Aug 05, 2025