{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:04Z","timestamp":1755219844443,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643686080"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>A significant proportion of rheumatoid arthritis patients experience multiple organ-related complications, severely affecting their quality of life. Establishing a dynamic prediction model that adequately considers the associative relationships of complications can contribute to the health management of patients. In this study, we propose to introduce a complication association enhancement module into the dynamic time-series prediction model to improve its performance. This method captures the triggering and dependency relationships between complications, reveals comorbidity interactions, and identifies high-risk complication combinations through clustering. We identified a cluster of comorbidities consisting of interstitial lung lesions, pulmonary hypertension, and cardiovascular disease and achieved better predictive performance than previously proposed methods on the CREDIT dataset (Macro accuracy=0.978 Micro F1=0.755 Micro AUC=0.910). To the best of our knowledge, this is the first study to introduce disease associations in dynamic medical time-series data to enhance early warning of complications in rheumatoid arthritis.<\/jats:p>","DOI":"10.3233\/shti251021","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:21Z","timestamp":1754566701000},"source":"Crossref","is-referenced-by-count":0,"title":["CARE-Former: Enhancing Prediction of Comorbidities in Rheumatoid Arthritis via Asymmetric Complication Associations"],"prefix":"10.3233","author":[{"given":"Huayu","family":"Yu","sequence":"first","affiliation":[{"name":"College of Biomedical Engineering and Instrument Science, Zhejiang University, Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Hangzhou 310027, China"}]},{"given":"Yu","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering and Instrument Science, Zhejiang University, Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Hangzhou 310027, China"}]},{"given":"Shuyu","family":"Ouyang","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering and Instrument Science, Zhejiang University, Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Hangzhou 310027, China"}]},{"given":"Dubai","family":"Li","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering and Instrument Science, Zhejiang University, Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Hangzhou 310027, China"}]},{"given":"Danyang","family":"Tong","sequence":"additional","affiliation":[{"name":"Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou 311121, China"}]},{"given":"Tianshu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou 311121, China"}]},{"given":"Nan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science and Technology, State Key Laboratory of Complex Severe and Rare Diseases, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China"}]},{"given":"Qian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science and Technology, State Key Laboratory of Complex Severe and Rare Diseases, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China"}]},{"given":"Xinping","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science and Technology, State Key Laboratory of Complex Severe and Rare Diseases, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China"}]},{"given":"Jingsong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering and Instrument Science, Zhejiang University, Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Hangzhou 310027, China"},{"name":"Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou 311121, China"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251021","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:38:21Z","timestamp":1754566701000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251021"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251021","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}