{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T22:24:42Z","timestamp":1758407082436},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T00:00:00Z","timestamp":1652659200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,16]]},"abstract":"<jats:p>Background: In recent years, there has been a rising interest in the application of deep neural networks (DNN) for the delineation of the electrocardiogram (ECG). Objectives: A variety of DNN architectures has been investigated in a 5-fold cross-validation approach. Results: The best performing network achieved 100% sensitivity and &gt;97% positive predictive value for all ECG waves. Conclusion: Our DNN could achieve similar classification performance as other DNN approaches described in the literature at a reduced computational cost.<\/jats:p>","DOI":"10.3233\/shti220356","type":"book-chapter","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T07:27:11Z","timestamp":1653031631000},"source":"Crossref","is-referenced-by-count":1,"title":["Electrocardiogram Delineation Using Deep Neural Networks"],"prefix":"10.3233","author":[{"given":"Max","family":"Haberbusch","sequence":"first","affiliation":[{"name":"Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria"},{"name":"Ludwig Boltzmann Institute for Cardiovascular Engineering, Vienna, Austria"}]},{"given":"Lisa A.","family":"Bernardo","sequence":"additional","affiliation":[{"name":"Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria"},{"name":"Scuola Superiore Sant\u2019Anna, Pisa, Italy"}]},{"given":"Laura","family":"Galassi","sequence":"additional","affiliation":[{"name":"Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria"},{"name":"Scuola Superiore Sant\u2019Anna, Pisa, Italy"}]},{"given":"Calogero M.","family":"Oddo","sequence":"additional","affiliation":[{"name":"Scuola Superiore Sant\u2019Anna, Pisa, Italy"},{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, Pisa, Italy"}]},{"given":"Francesco","family":"Moscato","sequence":"additional","affiliation":[{"name":"Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria"},{"name":"Ludwig Boltzmann Institute for Cardiovascular Engineering, Vienna, Austria"},{"name":"Austrian Cluster for Tissue Regeneration, Vienna, Austria"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","dHealth 2022"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220356","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T07:27:12Z","timestamp":1653031632000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220356"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,16]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220356","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,16]]}}}