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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Lee, Jong Taek Lee, JT 1 Elect & Telecommun Res Inst ETRI, Artificial Intelligence Applicat Res Sect, Daegu, South Korea 0000-0002-6962-3148 Lee, Jong Taek teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Park, Eunhee Park, E 2 Kyungpook Natl Univ, Sch Med, Dept Rehabil Med, 807 Hoguk Ro, Daegu 41404, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Park, Eunhee Park, E 2 Kyungpook Natl Univ Hosp, Dept Rehabil Med, Daegu, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Hwang, Jong-Moon Hwang, JM 3 Kyungpook Natl Univ, Sch Med, Dept Rehabil Med, 807 Hoguk Ro, Daegu 41404, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Hwang, Jong-Moon Hwang, JM 3 Kyungpook Natl Univ Hosp, Dept Rehabil Med, Daegu, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Jung, Tae-Du Jung, TD 4 교신저자 Kyungpook Natl Univ, Sch Med, Dept Rehabil Med, 807 Hoguk Ro, Daegu 41404, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Jung, Tae-Du Jung, TD 4 교신저자 Kyungpook Natl Univ Hosp, Dept Rehabil Med, Daegu, South Korea teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study Park, Donghwi Park, D 5 교신저자 Univ Ulsan, Coll Med, Ulsan Univ Hosp, Dept Phys Med & Rehabil, 877 Bangeojinsunhwando Ro, Ulsan 44033, South Korea GYQ-6185-2022 Park, Donghwi teeed0522@hanmail.net;bdome@hanmail.net;
Machine learning based approach for multimedia surveillance during fire emergencies Saeed, Faisal Saeed, F 1 Kyungpook Natl Univ, Dept Comp Sci & Engn, Daegu 702701, South Korea HNT-0710-2023 Saeed, Faisal 0000-0002-2822-1708 Saeed, Faisal bscsfaisal821@gmail.com;paul.editor@gmail.com;hongwh@knu.ac.kr;notsools@gmail.com;
Machine learning based approach for multimedia surveillance during fire emergencies Paul, Anand Paul, A 2 교신저자 Kyungpook Natl Univ, Dept Comp Sci & Engn, Daegu 702701, South Korea V-6724-2017 Paul, Anand 0000-0003-3115-2325 Paul, Anand bscsfaisal821@gmail.com;paul.editor@gmail.com;hongwh@knu.ac.kr;notsools@gmail.com;
Machine learning based approach for multimedia surveillance during fire emergencies Hong, Won Hwa Hong, WH 3 Kyungpook Natl Univ, Sch Architectural Civil Environm & Energy Engn, Daegu 702701, South Korea bscsfaisal821@gmail.com;paul.editor@gmail.com;hongwh@knu.ac.kr;notsools@gmail.com;
Machine learning based approach for multimedia surveillance during fire emergencies Seo, Hyuncheol Seo, H 4 Kyungpook Natl Univ, Sch Architectural Civil Environm & Energy Engn, Daegu 702701, South Korea ABC-5117-2020 Seo, Hyuncheol 0000-0002-3361-2316 Seo, HyunCheol bscsfaisal821@gmail.com;paul.editor@gmail.com;hongwh@knu.ac.kr;notsools@gmail.com;
Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07) Jang, Bum-Sup Jang, BS 1 Seoul Natl Univ, Dept Radiat Oncol, Bundang Hosp, Seongnam 13620, South Korea 0000-0002-7064-9855 Jang, Bum-Sup bigwiz83@gmail.com;parkukkyu@daum.net;hyck9004@naver.com;ihkim@snu.ac.kr;dh8lim@skku.edu;shinhyungpark@knu.ac.kr;drleejuhye@gmail.com;jh.chang@snu.ac.kr;kwancho@ncc.re.kr;jhkim@dsmc.or.kr;leonard.sunwoo@gmail.com;verocay1@snu.ac.kr;inah228@snu.ac.kr;
Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07) Park, Andrew J. Park, AJ 2 SELVAS AI Inc, Artificial Intelligence Res & Dev Lab, Seoul 08594, South Korea bigwiz83@gmail.com;parkukkyu@daum.net;hyck9004@naver.com;ihkim@snu.ac.kr;dh8lim@skku.edu;shinhyungpark@knu.ac.kr;drleejuhye@gmail.com;jh.chang@snu.ac.kr;kwancho@ncc.re.kr;jhkim@dsmc.or.kr;leonard.sunwoo@gmail.com;verocay1@snu.ac.kr;inah228@snu.ac.kr;
Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07) Jeon, Seung Hyuck Jeon, SH 3 Korea Adv Inst Sci & Technol, Grad Sch Med Sci & Engn, Daejeon 34141, South Korea bigwiz83@gmail.com;parkukkyu@daum.net;hyck9004@naver.com;ihkim@snu.ac.kr;dh8lim@skku.edu;shinhyungpark@knu.ac.kr;drleejuhye@gmail.com;jh.chang@snu.ac.kr;kwancho@ncc.re.kr;jhkim@dsmc.or.kr;leonard.sunwoo@gmail.com;verocay1@snu.ac.kr;inah228@snu.ac.kr;
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