{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T16:52:15Z","timestamp":1757609535951,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643686158"}],"license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"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":[[2025,9,3]]},"abstract":"<jats:p>Introduction: Entering the content of manually filled documents in the database of an electronic clinical Trial Master File (eTMF) is a tedious and time-consuming task. Methods: We report experiments for automatic transcription with an optical document recognition pipeline and a web-based (global) and a local multimodal large language model (LLM). Results: Different approaches are best suited for different column types of the table-based documents. Conclusions: Drastic time savings compared to manual transcription are possible.<\/jats:p>","DOI":"10.3233\/shti251378","type":"book-chapter","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T10:24:18Z","timestamp":1756895058000},"source":"Crossref","is-referenced-by-count":0,"title":["Transcription of Handwritten Forms for Medical Study Documentation"],"prefix":"10.3233","author":[{"given":"Luca","family":"Kohlhepp","sequence":"first","affiliation":[{"name":"CAIDAS (Center of AI and Data Science), Univ. W\u00fcrzburg, Germany"}]},{"given":"Sabine","family":"Busies","sequence":"additional","affiliation":[{"name":"iOMEDICO AG, Germany"}]},{"given":"Ute","family":"Zirrgiebel","sequence":"additional","affiliation":[{"name":"iOMEDICO AG, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7106-3223","authenticated-orcid":false,"given":"Frank","family":"Puppe","sequence":"additional","affiliation":[{"name":"CAIDAS (Center of AI and Data Science), Univ. W\u00fcrzburg, Germany"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","German Medical Data Sciences 2025: GMDS Illuminates Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251378","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T10:24:18Z","timestamp":1756895058000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251378"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"ISBN":["9781643686158"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251378","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2025,9,3]]}}}