Machine learning predicts stem cell transplant response in severe scleroderma.

Jennifer M FranksViktor MartyanovYue WangTammara A WoodAshley PinckneyLeslie J CroffordLynette Keyes-ElsteinDaniel E FurstEllen GoldmuntzMaureen D MayesPeter McSweeneyRichard A NashKeith M SullivanMichael L Whitfield

Published in: Annals of the rheumatic diseases (2020)

Participants from the fibroproliferative subset showed the most significant long-term benefit from HSCT compared with CYC. This study suggests that intrinsic subset stratification of patients may be used to identify patients with SSc who receive significant benefit from HSCT.

Keyphrases

stem cells
machine learning
end stage renal disease
newly diagnosed
ejection fraction
chronic kidney disease
systemic sclerosis
artificial intelligence
patient reported outcomes
rheumatoid arthritis
bone marrow
drug induced