biostudies-literatureUnknown11Mahdi MFIn this article, a new combination of an explainable machine learning approach with a fuzzy evaluation framework is proposed to improve the diagnostic performance and interpretation of rheumatic and autoimmune diseases. This work addresses three major challenges: (i) overlapping symptoms and complex clinical presentations, (ii) the lack of interpretability in traditional machine learning models, and (iii) the difficulty of selecting the best diagnosis model. To overcome these challenges, a new dataset was collected from Iraq's hospitals and health centers between 2019 and 2024. The size of dataset is 12,085 patients and includes 14 features in seven classes (rheumatoid arthritis, reactive arthritis, ankylosing spondylitis, Sjogren syndrome, systemic lupus erythematosus, psoriatic arthritisPeerJ. Computer sciencee3096https://www.ebi.ac.uk/biostudies/studies/S-EPMC12453786biostudies-literatureFuzzy evaluation and explainable machine learning for diagnosis of rheumatic and autoimmune diseases.PMC12453786Mahdi MFJahani AAbd DHfalseFuzzy evaluation and explainable machine learning for diagnosis of rheumatic and autoimmune diseases.In this article, a new combination of an explainable machine learning approach with a fuzzy evaluation framework is proposed to improve the diagnostic performance and interpretation of rheumatic and autoimmune diseases. This work addresses three major challenges: (i) overlapping symptoms and complex clinical presentations, (ii) the lack of interpretability in traditional machine learning models, and (iii) the difficulty of selecting the best diagnosis model. To overcome these challenges, a new dataset was collected from Iraq's hospitals and health centers between 2019 and 2024. The size of dataset is 12,085 patients and includes 14 features in seven classes (rheumatoid arthritis, reactive arthritis, ankylosing spondylitis, Sjogren syndrome, systemic lupus erythematosus, psoriatic arthritis2025-01-01T00:00:00Z20252026-04-30T03:20:37.143Z2026-04-30T03:12:07.25ZS-EPMC124537864098935910.7717/peerj-cs.3096