{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:38:34Z","timestamp":1779403114517,"version":"3.53.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686615","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"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":[[2026,5,21]]},"abstract":"<jats:p>Integrating heterogeneous data sources is vital for developing and validating robust medical machine learning models. Although the 12-lead format is standard in clinical electrocardiography (ECG), many datasets include only single-lead or vectorcardiogram (VCG) recordings. This study examines the transferability of 12-lead ECG data to VCG representations. Results show that ECG-VCG transfer depends on the acquisition system, whether clinical or Holter-based, and that the V6-X lead configuration achieves the most stable cross-lead performance.<\/jats:p>","DOI":"10.3233\/shti260213","type":"book-chapter","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:58:21Z","timestamp":1779400701000},"source":"Crossref","is-referenced-by-count":0,"title":["Generalization of ML Models Between ECG and VCG Representation"],"prefix":"10.3233","author":[{"given":"Lucas","family":"Plagwitz","sequence":"first","affiliation":[{"name":"Institute of Medical Informatics, University of M\u00fcnster"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucas","family":"Bickmann","sequence":"additional","affiliation":[{"name":"Institute for Medical Data Science, Otto-von-Guericke University Magdeburg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian","family":"Varghese","sequence":"additional","affiliation":[{"name":"Institute for Medical Data Science, Otto-von-Guericke University Magdeburg"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominik","family":"Heider","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, University of M\u00fcnster"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lars","family":"Eckardt","sequence":"additional","affiliation":[{"name":"Clinic for Cardiology II: Electrophysiology, University Hospital M\u00fcnster"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonius","family":"B\u00fcscher","sequence":"additional","affiliation":[{"name":"Institute of Medical Informatics, University of M\u00fcnster"},{"name":"Clinic for Cardiology II: Electrophysiology, University Hospital M\u00fcnster"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Opening the Personal Gate between Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260213","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:58:21Z","timestamp":1779400701000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260213"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"ISBN":["9781643686615"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260213","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,21]]}}}