{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T14:38:14Z","timestamp":1777905494558,"version":"3.51.4"},"reference-count":31,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T00:00:00Z","timestamp":1625184000000},"content-version":"vor","delay-in-days":182,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100016270","name":"Global Challenges Research Fund","doi-asserted-by":"publisher","award":["P202PF11"],"award-info":[{"award-number":["P202PF11"]}],"id":[{"id":"10.13039\/100016270","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p><jats:italic>Aim<\/jats:italic>. This study proposes a new artificial intelligence model based on cardiovascular computed tomography for more efficient and precise recognition of Tetralogy of Fallot (TOF). <jats:italic>Methods<\/jats:italic>. Our model is a structurally optimized stochastic pooling convolutional neural network (SOSPCNN), which combines stochastic pooling, structural optimization, and convolutional neural network. In addition, multiple\u2010way data augmentation is used to overcome overfitting. Grad\u2010CAM is employed to provide explainability to the proposed SOSPCNN model. Meanwhile, both desktop and web apps are developed based on this SOSPCNN model. <jats:italic>Results<\/jats:italic>. The results on ten runs of 10\u2010fold crossvalidation show that our SOSPCNN model yields a sensitivity of 92.25 \u00b1 2.19, a specificity of 92.75 \u00b1 2.49, a precision of 92.79 \u00b1 2.29, an accuracy of 92.50 \u00b1 1.18, an F1 score of 92.48 \u00b1 1.17, an MCC of 85.06 \u00b1 2.38, an FMI of 92.50 \u00b1 1.17, and an AUC of 0.9587. <jats:italic>Conclusion<\/jats:italic>. The SOSPCNN method performed better than three state\u2010of\u2010the\u2010art TOF recognition approaches.<\/jats:p>","DOI":"10.1155\/2021\/5792975","type":"journal-article","created":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T22:35:07Z","timestamp":1625265307000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["SOSPCNN: Structurally Optimized Stochastic Pooling Convolutional Neural Network for Tetralogy of Fallot Recognition"],"prefix":"10.1155","volume":"2021","author":[{"given":"Shui-Hua","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaihong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianshu","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steven L.","family":"Fernandes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghua","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4870-1493","authenticated-orcid":false,"given":"Yu-Dong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5296-283X","authenticated-orcid":false,"given":"Jian","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,7,2]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12041-020-01257-z"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpcardiol.2020.100643"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1055\/s-0039-1693727"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.33963\/KP.15644"},{"key":"e_1_2_10_5_2","article-title":"Coronary artery anomalies in Tetralogy of Fallot patients undergoing CT angiography at a tertiary care hospital","volume":"12","author":"Ashraf T.","year":"2020","journal-title":"Cureus"},{"key":"e_1_2_10_6_2","first-page":"120","article-title":"Comparison of whole-body MRI and 68Ga-DOTATATE PET-CT findings in patients with suspected peritoneal metastases from neuroendocrine tumors","volume":"33","author":"Engbersen M.","year":"2021","journal-title":"Journal of Neuroendocrinology"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14609"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21028-0_23"},{"key":"e_1_2_10_9_2","doi-asserted-by":"crossref","unstructured":"GiannakidisA. 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