{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T10:36:37Z","timestamp":1793010997379,"version":"4.5.0"},"reference-count":35,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100012547","name":"Natural Science Foundation of Guangxi Zhuang Autonomous Region","doi-asserted-by":"publisher","award":["2025GXNSFBA069134"],"award-info":[{"award-number":["2025GXNSFBA069134"]}],"id":[{"id":"10.13039\/100012547","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Int J of Rheum Dis"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Accurate diagnosis and assessment of hip involvement are important for the clinical management of ankylosing spondylitis (AS). This study aimed to develop and internally validate an artificial intelligence\u2013based Ensemble Scoring System (ESS) for AS diagnosis and hip\u2010disease severity assessment and to explore its association with heterogeneous immune\u2010cell infiltration and age at first documented severe hip involvement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 5721 patients with pelvic radiographs and linked clinical records were retrospectively included. Participants were divided into training and held\u2010out validation cohorts at a 7:3 ratio strictly at the patient level, with no patient or image overlap. Deep\u2010learning features extracted by a convolutional neural network were integrated with clinical variables using XGBoost to construct task\u2010specific ensemble deep\u2010learning (EDL) models. Exploratory proteomic, transcriptomic, single\u2010cell RNA\u2010sequencing, immunohistochemical, and peripheral\u2010blood analyses were performed to investigate AS\u2010related immune infiltration. An exploratory immune ensemble (IE) score was constructed using the monocyte proportion and EDL score. Kaplan\u2013Meier analysis was used to examine the association between the IE score and age at severe hip involvement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The EDL model achieved AUCs of 0.978 for distinguishing AS from non\u2010AS, 0.990 for identifying hip arthropathy among patients with AS, and 0.996 for identifying BASRI\u2010Hip grade \u2265\u20093 among patients with hip arthropathy. Monocyte percentage was an influential feature across the three EDL classification tasks. Exploratory multiomics and immunohistochemical analyses showed higher LYN expression in AS than in the corresponding non\u2010AS fracture\u2010control groups and suggested that LYN expression was concentrated predominantly in monocytes. A high IE score was associated with earlier severe hip involvement, with estimated median ages at first documented severe hip involvement of 36 and 50\u2009years in the high\u2010 and low\u2010IE\u2010score groups, respectively. This finding represents exploratory risk stratification and does not establish independent prediction of biological disease progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The ESS showed strong internal validation performance for AS diagnosis and hip\u2010disease severity classification. Exploratory analyses linked LYN dysregulation in monocytes with heterogeneous immune infiltration, while the IE score was associated with earlier severe hip involvement. Prospective multicenter external validation is required before clinical application.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1756-185x.70888","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T07:46:25Z","timestamp":1791013585000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence\u2013Based Scoring System and Exploratory Multiomics in Ankylosing Spondylitis: Hip Severity and Age\u2010at\u2010Severe\u2010Hip\u2010Involvement Stratification"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9841-759X","authenticated-orcid":false,"given":"Chenxing","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Spine Surgery The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences  Nanning Guangxi P. R. 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