{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T13:00:49Z","timestamp":1780405249092,"version":"3.54.1"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T00:00:00Z","timestamp":1608249600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T00:00:00Z","timestamp":1608249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R43 HL145896"],"award-info":[{"award-number":["R43 HL145896"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>An understanding of left ventricle (LV) mechanics is fundamental for designing better preventive, diagnostic, and treatment strategies for improved heart function. Because of the costs of clinical and experimental studies to treat and understand heart function, respectively, in-silico models play an important role. Finite element (FE) models, which have been used to create in-silico LV models for different cardiac health and disease conditions, as well as cardiac device design, are time-consuming and require powerful computational resources, which limits their use when real-time results are needed. As an alternative, we sought to use deep learning (DL) for LV in-silico modeling. We used 80 four-chamber heart FE models for feed forward, as well as recurrent neural network (RNN) with long short-term memory (LSTM) models for LV pressure and volume. We used 120 LV-only FE models for training LV stress predictions. The active material properties of the myocardium and time were features for the LV pressure and volume training, and passive material properties and element centroid coordinates were features of the LV stress prediction models. For six test FE models, the DL error for LV volume was 1.599\u2009\u00b1\u20091.227\u00a0ml, and the error for pressure was 1.257\u2009\u00b1\u20090.488\u00a0mmHg; for 20 LV FE test examples, the mean absolute errors were, respectively, 0.179\u2009\u00b1\u20090.050 for myofiber, 0.049\u2009\u00b1\u20090.017 for cross-fiber, and 0.039\u2009\u00b1\u20090.011\u00a0kPa for shear stress. After training, the DL runtime was in the order of seconds whereas equivalent FE runtime was in the order of several hours (pressure and volume) or 20\u00a0min (stress). We conclude that using DL, LV in-silico simulations can be provided for applications requiring real-time results.<\/jats:p>","DOI":"10.1038\/s41598-020-79191-4","type":"journal-article","created":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T11:04:12Z","timestamp":1608289452000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Application of feed forward and recurrent neural networks in simulation of left ventricular mechanics"],"prefix":"10.1038","volume":"10","author":[{"given":"Yaghoub","family":"Dabiri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Van der Velden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin L.","family":"Sack","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jenny S.","family":"Choy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julius M.","family":"Guccione","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghassan S.","family":"Kassab","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,12,18]]},"reference":[{"key":"79191_CR1","doi-asserted-by":"publisher","first-page":"1209","DOI":"10.1016\/j.jcmg.2015.08.006","volume":"8","author":"JK Min","year":"2015","unstructured":"Min, J. 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The remaining authors declare that they have no competing interests as defined by Nature Research, or other interests that might be perceived to influence the results and\/or discussion reported in this paper.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"22298"}}