{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T13:40:29Z","timestamp":1788961229261,"version":"build-2803163510"},"reference-count":28,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T00:00:00Z","timestamp":1642377600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Clinical Ultrasound"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>To evaluate if an automatic classification of rheumatoid arthritis (RA) metacarpophalangeal joint conditions in ultrasound images is feasible by deep learning (DL) method, to provide a more objective, automated, and fast way of RA diagnosis in clinical setting.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>DenseNet\u2010based DL model was used and both training and testing are implemented in TensorFlow 1.13.1 with Keras DL libraries. The area under curve (AUC), accuracy, sensitivity, and specificity values with 95% CIs were reported. The statistical analysis was performed by using scikit\u2010learn libraries in Python 3.7.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 1337 RA ultrasound images were acquired from 208 patients, the number of images is 313, 657, 178, and 189 in OESS Grade L0, L1, L2, and L3, respectively. In Classification Scenario 1\u00a0SP\u2010no versus SP\u2010yes, three experiments with region of interest of size 192\u2009\u00d7\u2009448 (Group 1), 96\u2009\u00d7\u2009224 (Group 2), and 96\u2009\u00d7\u2009224 stacked with pre\u2010segmented annotated mask of SP area (Group 3) as input achieve an AUC of 0.863 (95% CI: 0.809, 0.917), 0.861 (95% CI: 0.805, 0.916), and 0.886 (95% CI: 0.836, 0.936), respectively. In Classification Scenario 2 Healthy versus Diseased, experiments in Group 1, Group 2 and Group 3 achieve an AUC of 0.848 (95% CI: 0.799, 0.896), 0.864 (95% CI: 0.819, 0.909), and 0.916 (95% CI: 0.883, 0.952), respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We combined DenseNet model with ultrasound images for RA condition assessment. The feasibility of using DL to create an automatic RA condition classification system was also demonstrated. The proposed method can be an alternative to the initial screening of RA patients.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jcu.23143","type":"journal-article","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T16:20:29Z","timestamp":1642436429000},"page":"296-301","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["A deep learning classification of <scp>metacarpophalangeal joints<\/scp> synovial proliferation in rheumatoid arthritis by ultrasound images"],"prefix":"10.1002","volume":"50","author":[{"given":"Min","family":"Wu","sequence":"first","affiliation":[{"name":"Physical Examination Xintai People's Hospital  Tai'an Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5203-729X","authenticated-orcid":false,"given":"Huaiuy","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Ultrasound The Second Clinical Medical 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China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4558-4885","authenticated-orcid":false,"given":"Fajin","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Ultrasound The Second Clinical Medical College\uff0cJinan University  Guangdong China"},{"name":"The First Affiliated Hospital Southern University of Science and Technology, Shenzhen People's Hospital  Shenzhen Guangdong China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0889-857X(21)00886-3"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.0000054612.26458.B2"},{"issue":"5","key":"e_1_2_11_4_1","article-title":"Health\u2010related quality of life in fibromyalgia patients: a comparison with rheumatoid arthritis patients and the general population using the SF\u201036 health 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