{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T04:51:12Z","timestamp":1788324672953,"version":"build-2803163510"},"reference-count":50,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T00:00:00Z","timestamp":1637020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004770","name":"University of Parma","doi-asserted-by":"publisher","award":["FIL 2018-2021"],"award-info":[{"award-number":["FIL 2018-2021"]}],"id":[{"id":"10.13039\/501100004770","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003407","name":"Ministry of Education, Universities and Research","doi-asserted-by":"publisher","award":["2017AXL54F_002"],"award-info":[{"award-number":["2017AXL54F_002"]}],"id":[{"id":"10.13039\/501100003407","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>The human right ventricle is barely monitored during open-chest surgery due to the absence of intraoperative imaging techniques capable of elaborating its complex function. Accordingly, artificial intelligence could not be adopted for this specific task. We recently proposed a video-based approach for the real-time evaluation of the epicardial kinematics to support medical decisions. Here, we employed two supervised machine learning algorithms based on our technique to predict the patients\u2019 outcomes before chest closure. Videos of the beating hearts were acquired before and after pulmonary valve replacement in twelve Tetralogy of Fallot patients and recordings were properly labeled as the \u201cunhealthy\u201d and \u201chealthy\u201d classes. We extracted frequency-domain-related features to train different supervised machine learning models and selected their best characteristics via 10-fold cross-validation and optimization processes. Decision surfaces were built to classify two additional patients having good and unfavorable clinical outcomes. The k-nearest neighbors and support vector machine showed the highest prediction accuracy; the patients\u2019 class was identified with a true positive rate \u226595% and the decision surfaces correctly classified the additional patients in the \u201chealthy\u201d (good outcome) or \u201cunhealthy\u201d (unfavorable outcome) classes. We demonstrated that classifiers employed with our video-based technique may aid cardiac surgeons in decision making before chest closure.<\/jats:p>","DOI":"10.3390\/jcm10225330","type":"journal-article","created":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T11:32:03Z","timestamp":1637062323000},"page":"5330","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Artificial Intelligence Supports Decision Making during Open-Chest Surgery of Rare Congenital Heart Defects"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4730-2458","authenticated-orcid":false,"given":"Francesco Paolo","family":"Lo Muzio","sequence":"first","affiliation":[{"name":"Department of Surgery, Dentistry, Pediatrics and Gynecology, University of Verona, 37134 Verona, Italy"},{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5085-4819","authenticated-orcid":false,"given":"Giacomo","family":"Rozzi","sequence":"additional","affiliation":[{"name":"Department of Surgery, Dentistry, Pediatrics and Gynecology, University of Verona, 37134 Verona, Italy"},{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"},{"name":"Humanitas Research Hospital\u2014IRCCS, Via Manzoni 56, 20089 Rozzano, MI, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0346-8410","authenticated-orcid":false,"given":"Stefano","family":"Rossi","sequence":"additional","affiliation":[{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni Battista","family":"Luciani","sequence":"additional","affiliation":[{"name":"Department of Surgery, Dentistry, Pediatrics and Gynecology, University of Verona, 37134 Verona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1060-978X","authenticated-orcid":false,"given":"Ruben","family":"Foresti","sequence":"additional","affiliation":[{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aderville","family":"Cabassi","sequence":"additional","affiliation":[{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5587-4632","authenticated-orcid":false,"given":"Lorenzo","family":"Fassina","sequence":"additional","affiliation":[{"name":"Department of Electrical, Computer and Biomedical Engineering (DIII), University of Pavia, 27100 Pavia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4058-4368","authenticated-orcid":false,"given":"Michele","family":"Miragoli","sequence":"additional","affiliation":[{"name":"Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy"},{"name":"Humanitas Research Hospital\u2014IRCCS, Via Manzoni 56, 20089 Rozzano, MI, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1136\/svn-2017-000101","article-title":"Artificial intelligence in healthcare: Past, present and future","volume":"2","author":"Jiang","year":"2017","journal-title":"Stroke Vasc. 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