{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T23:02:44Z","timestamp":1793142164089,"version":"4.5.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T00:00:00Z","timestamp":1730073600000},"content-version":"vor","delay-in-days":27,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Youth Fund Program","award":["ZHUPEI2022-010"],"award-info":[{"award-number":["ZHUPEI2022-010"]}]},{"name":"Youth Fund Program","award":["2023ZSQN38"],"award-info":[{"award-number":["2023ZSQN38"]}]},{"DOI":"10.13039\/501100010108","name":"Zhongshan Hospital","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003347","name":"Fudan University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003347","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20190808115419619"],"award-info":[{"award-number":["JCYJ20190808115419619"]}]},{"name":"Shenzhen Science and Technology Program","award":["20220810145705001"],"award-info":[{"award-number":["20220810145705001"]}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12326619"],"award-info":[{"award-number":["12326619"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306183"],"award-info":[{"award-number":["62306183"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Guandong","award":["2024A1515030143"],"award-info":[{"award-number":["2024A1515030143"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Aims<\/jats:title>\n                  <jats:p>To address the limitations of traditional diagnostic methods for mitral valve prolapse (MVP), specifically fibroelastic deficiency (FED) and Barlow\u2019s disease (BD), by introducing an automated diagnostic approach utilizing multi-view echocardiographic sequences and deep learning.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods and results<\/jats:title>\n                  <jats:p>An echocardiographic data set, collected from Zhongshan Hospital, Fudan University, containing apical 2 chambers (A2C), apical 3 chambers (A3C), and apical 4 chambers (A4C) views, was employed to train the deep learning models. We separately trained view-specific and view-agnostic deep neural network models, which were denoted as MVP-VS and MVP view-agonistic (VA), for MVP diagnosis. Diagnostic accuracy, precision, sensitivity, F1-score, and specificity were evaluated for both BD and FED phenotypes. MVP-VS demonstrated an overall diagnostic accuracy of 0.94 for MVP. In the context of BD diagnosis, precision, sensitivity, F1-score, and specificity were 0.83, 1.00, 0.90, and 0.92, respectively. For FED diagnosis, the metrics were 1.00, 0.83, 0.91, and 1.00. MVP-VA exhibited an overall accuracy of 0.95, with BD-specific metrics of 0.85, 1.00, 0.92, and 0.94 and FED-specific metrics of 1.00, 0.83, 0.91, and 1.00. In particular, the MVP-VA model using mixed views for training demonstrated efficient diagnostic performance, eliminating the need for repeated development of MVP-VS models and improving the efficiency of the clinical pipeline by using arbitrary views in the deep learning model.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>This study pioneers the integration of artificial intelligence into MVP diagnosis and demonstrates the effectiveness of deep neural networks in overcoming the challenges of traditional diagnostic methods. The efficiency and accuracy of the proposed automated approach suggest its potential for clinical applications in the diagnosis of valvular heart disease.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/ehjimp\/qyae086","type":"journal-article","created":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T06:03:20Z","timestamp":1730181800000},"source":"Crossref","is-referenced-by-count":3,"title":["Feasibility validation of automatic diagnosis of mitral valve prolapse from multi-view echocardiographic sequences based on deep neural network"],"prefix":"10.1093","volume":"2","author":[{"given":"Zijian","family":"Wu","sequence":"first","affiliation":[{"name":"National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University , 1066 Xueyuan Road, Shenzhen 518060 ,","place":["China"]},{"name":"Medical Ultrasound Image Computing (MUSIC) Laboratory, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"},{"name":"Marshall Laboratory of Biomedical Engineering, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyi","family":"Ge","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]},{"name":"Shanghai Institute of Medical Imaging, Fudan University , Shanghai ,","place":["China"]},{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengdan","family":"Ge","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]},{"name":"Shanghai Institute of Medical Imaging, Fudan University , Shanghai ,","place":["China"]},{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yumeng","family":"Xing","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Huadong Hospital, Fudan University , Shanghai 200040 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weipeng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2222-3147","authenticated-orcid":false,"given":"Lili","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7851-1623","authenticated-orcid":false,"given":"Yongshi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dehong","family":"Kong","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunqiang","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yixiu","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiyan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]},{"name":"Shanghai Institute of Medical Imaging, Fudan University , Shanghai ,","place":["China"]},{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wufeng","family":"Xue","sequence":"additional","affiliation":[{"name":"National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University , 1066 Xueyuan Road, Shenzhen 518060 ,","place":["China"]},{"name":"Medical Ultrasound Image Computing (MUSIC) Laboratory, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"},{"name":"Marshall Laboratory of Biomedical Engineering, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7697-9970","authenticated-orcid":false,"given":"Cuizhen","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]},{"name":"Shanghai Institute of Medical Imaging, Fudan University , Shanghai ,","place":["China"]},{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Ni","sequence":"additional","affiliation":[{"name":"National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University , 1066 Xueyuan Road, Shenzhen 518060 ,","place":["China"]},{"name":"Medical Ultrasound Image Computing (MUSIC) Laboratory, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"},{"name":"Marshall Laboratory of Biomedical Engineering, Shenzhen University, 1066 Xueyuan Road, Shenzhen 518037, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianhong","family":"Shu","sequence":"additional","affiliation":[{"name":"Department of Echocardiography, Zhongshan Hospital, Fudan University , No. 1609 Xietu Road, Xuhui District, Shanghai 200030 ,","place":["China"]},{"name":"Shanghai Institute of Medical Imaging, Fudan University , Shanghai ,","place":["China"]},{"name":"Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University , Shanghai 200030 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