New risk model is able to identify patients with a low risk of progression in systemic sclerosis.

Nina Marijn van LeeuwenMarc MauritsSophie LiemJacopo CiaffiNina Ajmone MarsanMaarten NinaberCornelia AllaartHenrike Gillet van DongenRobbert GoekoopThomas Wj Huizinga Rachel KnevelJeska De Vries-Bouwstra

Published in: RMD open (2021)

Our machine-learning-assisted model for progression enabled us to classify 29% of SSc patients as 'low risk'. In this group, annual assessment programmes could be less extensive than indicated by international guidelines.

Keyphrases

systemic sclerosis
machine learning
interstitial lung disease
end stage renal disease
ejection fraction
newly diagnosed
chronic kidney disease
prognostic factors
rheumatoid arthritis
deep learning
artificial intelligence
idiopathic pulmonary fibrosis