{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T23:42:21Z","timestamp":1793835741428,"version":"4.6.1"},"reference-count":25,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T00:00:00Z","timestamp":1767052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objective: In recent years, artificial intelligence (AI) has gained increasing prominence in the fields of diagnostic decision-making in medicine. The aim of this study was to compare multidisciplinary team (MDT: rheumatology, pulmonology, thoracic radiology) decisions with single-session plans generated by ChatGPT-4o. Methods: In this cross-sectional concordance study, adults (\u226518 years) with confirmed systemic autoimmune rheumatic disease (SARD) and having MDT decisions within the last 6 months were included. The study documented diagnostic, treatment, and monitoring decisions in cases of SARDs by recording answers to six essential questions: (1) What is the most likely clinical diagnosis? (2) What is the most likely radiological diagnosis? (3) Is there a need for anti-inflammatory treatment? (4) Is there a need for antifibrotic treatment? (5) Is drug-free follow-up appropriate? and (6) Are additional investigations required? Consequently, all evaluations were performed with ChatGPT-4o in a single-session format using a standardized single-prompt template, with the system blinded to MDT decisions. All data analyses in this study were conducted using the R programming language (version 4.3.2). An agreement between AI-generated and MDT decisions was assessed using Cohen\u2019s Kappa (\u03ba) statistic where \u03ba (kappa) values represent the level of agreement: &lt;0.20 = slight, 0.21\u20130.40 = fair, 0.41\u20130.60 = moderate, 0.61\u20130.80 = substantial, &gt;0.80 = almost perfect agreement. These analyses were performed using the irr and psych packages in R. Statistical significance of the models was evaluated through p-values, while overall model fit was assessed using the Likelihood Ratio Test. Results: A total of 47 patients were involved in this study, with a predominance of female patients (61.70%, n = 29). The mean age was 61.74 \u00b1 10.40 years. The most frequently observed diagnosis was rheumatoid arthritis (RA), accounting for 31.91% of cases (n = 15). This was followed by cases of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis, interstitial pneumonia with autoimmune features (IPAF), and sarcoidosis. The analyses indicate a statistically significant level of agreement across all decision types. For clinical diagnosis decisions, agreement was moderate (\u03ba = 0.52), suggesting that the AI system can reach partially consistent conclusions in diagnostic processes. The need for an immunosuppressive treatment and follow-up without medication decisions demonstrated a higher level of concordance, reaching the moderate-to-high range (\u03ba = 0.64 and \u03ba = 0.67, respectively). For antifibrotic treatment decisions, agreement was moderate (\u03ba = 0.49), while radiological diagnosis decisions also fell within the moderate range (\u03ba = 0.55). The lowest agreement\u2014though still moderate\u2014was observed in further investigation required decisions (\u03ba = 0.45). Conclusions: In patients with SARDs with pulmonary involvement, particularly in complex cases, concordance was observed between MDT decisions and AI-generated recommendations regarding prioritization of clinical and radiologic diagnoses, treatment selection, suitability for drug-free follow-up, and the need for further diagnostic investigations.<\/jats:p>","DOI":"10.3390\/diagnostics16010113","type":"journal-article","created":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T13:30:52Z","timestamp":1767187852000},"page":"113","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Concordance Between the Multidisciplinary Team and ChatGPT-4o Decisions: A Blinded, Cross-Sectional Concordance Study in Systemic Autoimmune Rheumatic Diseases"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8441-5219","authenticated-orcid":false,"given":"Firdevs","family":"Uluta\u015f","sequence":"first","affiliation":[{"name":"Division of Rheumatology, Department of Internal Medicine, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00f6ksel","family":"Alt\u0131n\u0131\u015f\u0131k","sequence":"additional","affiliation":[{"name":"Department of Pulmonology, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00fclay","family":"G\u00fcng\u00f6r","sequence":"additional","affiliation":[{"name":"Department of Radiology, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vefa","family":"\u00c7akmak","sequence":"additional","affiliation":[{"name":"Department of Radiology, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nil\u00fcfer","family":"Yi\u011fit","sequence":"additional","affiliation":[{"name":"Department of Pulmonology, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duygu","family":"Herek","sequence":"additional","affiliation":[{"name":"Department of Radiology, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Murat","family":"Yi\u011fit","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Department of Internal Medicine, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"U\u011fur","family":"Karasu","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Department of Internal Medicine, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Veli","family":"\u00c7obankara","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Department of Internal Medicine, Pamukkale University Faculty of Medicine, 20000 Denizli, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.autrev.2012.02.001","article-title":"Updated assessment of the prevalence, spectrum and case definition of autoimmune disease","volume":"11","author":"Hayter","year":"2012","journal-title":"Autoimmun. 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