{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:53Z","timestamp":1747216193366,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685335"}],"license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"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":[[2024,8,22]]},"abstract":"<jats:p>This paper presents a comprehensive workflow for integrating revolving events into the transitive sequential pattern mining (tSPM+) algorithm and Machine Learning for Health Outcomes (MLHO) framework, emphasizing best practices and pitfalls in its application. We emphasize feature engineering and visualization techniques, demonstrating their efficacy in capturing temporal relationships. Applied to an EGFR lung cancer cohort, our approach showcases reliable temporal insights even in a small dataset. This work highlights the importance of temporal nuances in healthcare data analysis, paving the way for improved disease understanding and patient care.<\/jats:p>","DOI":"10.3233\/shti240738","type":"book-chapter","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:32:01Z","timestamp":1724409121000},"source":"Crossref","is-referenced-by-count":0,"title":["Temporal Characterization and Visualization of Revolving Therapy-Events in Lung Cancer Patients"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4183-1287","authenticated-orcid":false,"given":"Jonas","family":"H\u00fcgel","sequence":"first","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Medical Informatics, G\u00f6ttingen, Germany"},{"name":"University of G\u00f6ttingen, Campus Institute Data Science, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2218-3974","authenticated-orcid":false,"given":"Donata A.","family":"Sch\u00e4fer","sequence":"additional","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Hematology and Medical Oncology, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8317-875X","authenticated-orcid":false,"given":"Jan J.","family":"Schneider","sequence":"additional","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Medical Informatics, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0599-3438","authenticated-orcid":false,"given":"Jiazi","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Medicine, Massachusetts General Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0204-8978","authenticated-orcid":false,"given":"Hossein","family":"Estiri","sequence":"additional","affiliation":[{"name":"Department of Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"name":"Clinical Augmented Intelligence Group, Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2018-5685","authenticated-orcid":false,"given":"Raphael","family":"Koch","sequence":"additional","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Hematology and Medical Oncology, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2579-0171","authenticated-orcid":false,"given":"Tobias R.","family":"Overbeck","sequence":"additional","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Hematology and Medical Oncology, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8188-3495","authenticated-orcid":false,"given":"Ulrich","family":"Sax","sequence":"additional","affiliation":[{"name":"University Medical Center G\u00f6ttingen, Department of Medical Informatics, G\u00f6ttingen, Germany"},{"name":"University of G\u00f6ttingen, Campus Institute Data Science, G\u00f6ttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Health and Informatics Innovations for Sustainable Health Care Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240738","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:32:02Z","timestamp":1724409122000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240738"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"ISBN":["9781643685335"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240738","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}