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This cross-sectional concordance study compared multidisciplinary team (rheumatology, pulmonology, thoracic radiology) decisions with single-session plans generated by ChatGPT-4o in adults with systemic autoimmune rheumatic diseases. Evaluations covered clinical and radiological diagnoses, treatment and drug-free follow-up needs, and additional investigations, using a blinded standardized prompt and Cohen’s Kappa for agreement.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/concordance-between-the-multidisciplinary-team-and-chatgpt-4o-decisions-a-blinded-cross-sectional-concordance-study-in-systemic-autoimmune-rheumatic-diseases/465479/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/concordance-between-the-multidisciplinary-team-and-chatgpt-4o-decisions-a-blinded-cross-sectional-concordance-study-in-systemic-autoimmune-rheumatic-diseases/465479.png","ImageObject",300,407,{"name":92,"@type":93},"\tCallum ","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-05","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What was the objective of this study?","Question",{"text":112,"@type":113},"To compare multidisciplinary team decisions with single-session plans generated by ChatGPT-4o for adults with confirmed systemic autoimmune rheumatic diseases.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What decisions were evaluated in the concordance assessment?",{"text":117,"@type":113},"Clinical diagnosis, radiological diagnosis, need for anti-inflammatory treatment, need for antifibrotic treatment, appropriateness of drug-free follow-up, and whether additional investigations were required.",{"name":119,"@type":110,"acceptedAnswer":120},"How was agreement between AI and the multidisciplinary team measured?",{"text":121,"@type":113},"Using Cohen’s Kappa (κ), with κ values interpreted as slight, fair, moderate, substantial, or almost perfect agreement ranges.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},465479,1790815547,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},137451211410,"https://ap-avatar.wpscdn.com/avatar/2000bb0a9246f588df?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786362646172706240","Article  \nConcordance Between the Multidisciplinary Team and ChatGPT-4o Decisions: A Blinded, Cross-Sectional Concordance Study in Systemic Autoimmune Rheumatic Diseases  \nFirdevs Uluta¸s 1, *, Göksel Altını¸sık 2, Gülay Güngör 3, Vefa Çakmak 3, Nilüfer Yi ˘git 2, Duygu Herek 3, Murat Yi ˘git 1, U ˘gur Karasu 1 and Veli Çobankara 1  \nAcademic Editor: Ayman El-Baz  \nReceived: 2 December 2025  \nRevised: 16 December 2025  \nAccepted: 25 December 2025  \nPublished: 30 December 2025  \nCopyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.  \n1 Division of Rheumatology, Department of Internal Medicine, Pamukkale University Faculty of Medicine, 20000 Denizli, Türkiye  \n2 Department of Pulmonology, Pamukkale University Faculty of Medicine, 20000 Denizli, Türkiye  \n3 Department of Radiology, Pamukkale University Faculty of Medicine, 20000 Denizli, Türkiye  \n* [Correspondence: firdevsulutas1014@gmail.com](Correspondence: firdevsulutas1014@gmail.com); Tel.: +90-5300944632  \nAbstract  \nBackground/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 (≥18 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’s Kappa (κ) statistic where κ (kappa) values represent the level of agreement: \u003C0.20 = slight, 0.21–0.40 = fair, 0.41–0.60 = moderate, 0.61–0.80 = substantial, >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 ± 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 (κ = 0.52), suggesting that the AI system can reach partially consistent conclusionsin 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 (κ = 0.64 and κ = 0.67, respectively) . For antifibrotic treatment decisions, agreement was moderate (κ = 0.49), while radiological diagnosis decisions also fell within the moderate range (κ = 0.55) . The lowest agreement—though still moderate—was observed in further investigation required","cbCaiuXD9GSn0tqO","https://ap.wps.com/l/cbCaiuXD9GSn0tqO","pdf",256038,14,"English","# Abstract\n## Background/Objective\n## Methods\n## Results\n## Conclusions\n# Introduction","[{\"question\":\"What was the objective of this study?\",\"answer\":\"To compare multidisciplinary team decisions with single-session plans generated by ChatGPT-4o for adults with confirmed systemic autoimmune rheumatic diseases.\"},{\"question\":\"What decisions were evaluated in the concordance assessment?\",\"answer\":\"Clinical diagnosis, radiological diagnosis, need for anti-inflammatory treatment, need for antifibrotic treatment, appropriateness of drug-free follow-up, and whether additional investigations were required.\"},{\"question\":\"How was agreement between AI and the multidisciplinary team measured?\",\"answer\":\"Using Cohen’s Kappa (κ), with κ values interpreted as slight, fair, moderate, substantial, or almost perfect agreement ranges.\"}]","Concordance Between the Multidisciplinary Team and ChatGPT-4o Decisions - A Blinded, Cross-Sectional Concordance Study in Systemic Autoimmune Rheumatic Diseases | PDF",1790769673,35]