A machine learning-based classification model for interstitial lung disease in rheumatoid arthritis - Takeaways - MDSpire

A machine learning-based classification model for interstitial lung disease in rheumatoid arthritis

  • By

  • Mingyao Li

  • Qiaoli Wang

  • Junfeng He

  • Xia Wang

  • Yangyang Xu

  • Liwei Yang

  • Lin Feng

  • May 14, 2026

  • 0 min

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  • 1

    A machine learning model was developed to classify rheumatoid arthritis-associated interstitial lung disease using routine clinical parameters.

  • 2

    The study included 410 RA patients, with 24.39% diagnosed with RA-ILD, highlighting the prevalence of this pulmonary complication.

  • 3

    Seven key features were identified for model construction, including age, smoking history, and specific laboratory markers.

  • 4

    The CatBoost model achieved the highest AUC of 0.784, demonstrating superior performance in RA-ILD classification compared to other models.

  • 5

    Both CatBoost and decision tree models showed promise for RA-ILD risk stratification, warranting further external validation.

Original Source(s)

A machine learning-based classification model for interstitial lung disease in rheumatoid arthritis

  • by Mingyao Li, Qiaoli Wang, Junfeng He, Xia Wang, Yangyang Xu, Liwei Yang, Lin Feng

  • May 14, 2026

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