MILAN, Italy — Two independent efforts to use artificial intelligence to predict the development of early rheumatoid arthritis from patients with signs and symptoms not meeting full disease criteria showed good, near expert-level accuracy, according to findings from two studies presented at the European Alliance of Associations for Rheumatology 2023 Annual Meeting.
The accuracy of the model was evaluated using the area under the receiver operator characteristic curve . The model that was trained using MR scans of the hands achieved a mean AUROC of 0.84 for distinguishing EAC from healthy subjects and 0.83 for distinguishing CSA from healthy subjects. The model trained using MR scans of both the hands and feet achieved a mean AUROC of 0.71 for distinguishing RA from non-RA cases in EAC.
Their objective is to validate this method more broadly, and to achieve that, they require collaboration with other hospitals. Up until now, they have primarily worked with a specific type of MR images, specifically extremity MR scans. These scans are only conducted in a few centers equipped with extremity MR scanners, which can accommodate only hands or feet.
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