{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:58Z","timestamp":1755219838677,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"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":[[2025,8,7]]},"abstract":"<jats:p>Brain response to command can be detected using task-based EEG. Insufficient evidence of brain response and prognosis remain happen in brain infarction. This preliminary study aimed to explore brain response in task-based electroencephalography (EEG) and the 6-month responsiveness in brain infarction. Interestingly, we detected brain response in 58.59% of clinically responsive patients and 6.25% of unresponsive patients. The presence of brain response in clinically unresponsive patient indicates brain activation despite the absence of responsiveness in Glasgow Coma Scale (GCS) assessment. This descriptive and comparison analysis highlights the utility of EEG-based machine learning to identify brain response in brain infarction patients, providing insights for further investigation related to brain injury prognosis, rehabilitation strategy, and management.<\/jats:p>","DOI":"10.3233\/shti251256","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:46:12Z","timestamp":1754567172000},"source":"Crossref","is-referenced-by-count":0,"title":["Brain Response and 6-Month Responsiveness Exploration in Brain Infarction Case: Preliminary Study"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4873-0291","authenticated-orcid":false,"given":"Sari Rahmawati Kusuma","family":"Dewi","sequence":"first","affiliation":[{"name":"Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, New Taipei City, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6497-4232","authenticated-orcid":false,"given":"Yu-Chuan (Jack)","family":"Li","sequence":"additional","affiliation":[{"name":"Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, New Taipei City, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9624-9705","authenticated-orcid":false,"given":"Ming-Ching","family":"Lin","sequence":"additional","affiliation":[{"name":"Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, New Taipei City, Taiwan"},{"name":"Department of Neurosurgery, Wan Fang Hospital, Taipei Medical University, New Taipei City, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251256","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:46:12Z","timestamp":1754567172000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251256"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251256","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}