{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T05:06:52Z","timestamp":1788930412911,"version":"build-2803163510"},"reference-count":81,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Clin. Med.","JCM"],"abstract":"<jats:p>Artificial intelligence (AI) and machine learning (ML) are transforming the landscape of rheumatological and systemic inflammatory disease management, offering unprecedented capacity to integrate complex, multidimensional data for diagnostic support, disease monitoring, and therapeutic decision-making. This comprehensive narrative review, based on a non-systematic literature search of PubMed\/MEDLINE and Google Scholar combined with the authors\u2019 clinical expertise, provides a clinically oriented synthesis of current and emerging AI applications across the full spectrum of immune-mediated inflammatory diseases\u2014including rheumatoid arthritis, systemic lupus erythematosus, vasculitis, inflammatory bowel disease, psoriatic arthritis, systemic sclerosis, inflammatory myopathies, and sarcoidosis\u2014with particular attention to applications that have demonstrated or are approaching clinical utility. We discuss deep learning-based image analysis, natural language processing of electronic health records, multi-omic biomarker discovery, and the application of Fourier transform-based signal processing to biological time series as a novel approach to continuous disease monitoring. Fourier transform methods\u2014already foundational in MRI reconstruction, cardiac electrophysiology, and clinical neurophysiology\u2014are here systematically extended to rheumatological and inflammatory disease signals, including accelerometry, electromyography, heart rate variability, and longitudinal biomarker time series. The phenomenon of large language model hallucination\u2014particularly critical in rare inflammatory diseases\u2014is addressed alongside retrieval-augmented generation as a mitigation strategy. We further argue that AI-driven methods do not merely improve the interpretation of clinical data, but fundamentally expand what is observable\u2014with profound epistemological implications for clinical knowledge transmitted through generations of medical tradition. Ethical considerations and future directions toward precision inflammatory disease medicine are outlined.<\/jats:p>","DOI":"10.3390\/jcm15176864","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T17:25:56Z","timestamp":1788542756000},"page":"6864","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence and Machine Learning in Rheumatology and Systemic Inflammatory Diseases: From Pattern Recognition to Signal Analysis and Clinical Decision Support"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1174-2849","authenticated-orcid":false,"given":"Matteo","family":"Colina","sequence":"first","affiliation":[{"name":"Rheumatology Service, Section of Internal Medicine, Department of Medicine and Oncology, Ospedale Santa Maria della Scaletta, 40026 Imola, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4033-4019","authenticated-orcid":false,"given":"Roberto","family":"Diversi","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic and Information Engineering, University of Bologna, Viale del Risorgimento 2, 40236 Bologna, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1873","DOI":"10.1093\/rheumatology\/keae521","article-title":"Diagnostic Delay in Patients from the International Map of Axial Spondyloarthritis: Geographic, Sociodemographic and Disease-Related Factors","volume":"64","author":"Poddubnyy","year":"2025","journal-title":"Rheumatology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1759720X251343579","DOI":"10.1177\/1759720X251343579","article-title":"Current Application, Possibilities, and Challenges of Artificial Intelligence in the Management of Rheumatoid Arthritis, Axial Spondyloarthritis, and Psoriatic Arthritis","volume":"17","author":"Bilgin","year":"2025","journal-title":"Ther. 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