Predicting rheumatoid arthritis progression from seronegative undifferentiated arthritis using machine learning: a deep learning model trained on the KURAMA cohort and externally validated with the ANSWER cohort

Predicting rheumatoid arthritis progression from seronegative undifferentiated arthritis using machine learning: a deep learning model trained on the KURAMA cohort and externally validated with the ANSWER cohort

Abstract Background Undifferentiated arthritis (UA) often develops into rheumatoid arthritis (RA), but predicting disease progression from seronegative UA remains challenging because seronegative RA often does not meet the classification criteria. This study aims to build a machine learning (ML) mod...

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Main Authors: Takayuki Fujii, Koichi Murata, Hirohiko Kohjitani, Akira Onishi, Kosaku Murakami, Masao Tanaka, Wataru Yamamoto, Koji Nagai, Ayaka Yoshikawa, Yuki Etani, Yasutaka Okita, Naofumi Yoshida, Hideki Amuro, Tadashi Okano, Yo Ueda, Takaichi Okano, Ryota Hara, Motomu Hashimoto, Akio Morinobu, Shuichi Matsuda
Format: Article
Language:English
Published: BMC 2025-03-01
Series:Arthritis Research & Therapy
Online Access:https://doi.org/10.1186/s13075-025-03541-8
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https://doi.org/10.1186/s13075-025-03541-8

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