An interpretable machine learning model for diagnosis of various cardiac arrhythmias using a justified single-lead electrocardiography classification algorithm

[Speaker] Mi Jin Kim
Mijin Kim, MD1*, Otto van Koert2,3*, PhD, Seong-Ho Kong, MD, PhD2,4, Seung-Young Oh, MD 4,6, Won Kyeong Jeon, MD5, Taejin Paik3, Philip Choi3, Jae-hu Jeon7, Joong-Sik Hong7, Wan-Joong Kim7, Myung-Jin Cha, MD, PhD1#, Woong Kook, PhD2,3#
1. Division of Cardiology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea 2. AI Institute, Seoul National University, Seoul, South Korea 3. Department of Mathematical Sciences, Seoul National University, Seoul, South Korea 4. Department of Surgery, Seoul National University Hospital and Seoul National University College of Medicine, Seoul, South Korea 5 Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea 6 Department of Critical Care Medicine, Seoul National University Hospital 7 Medifarmsoft Co., Ltd., Seoul, South Korea

Association of genetically predicted smoking traits and alcohol consumption with the risk of atrial fibrillation: Mendelian randomization study.

[Speaker] Seunghoon Cho
Seunghoon Cho, MD;¹ Pil-Sung Yang, MD;² Daehoon Kim, MD;¹ Seng Chan You, MD, MS;³ Jung-Hoon Sung, MD;²Eunsun Jang, MS;¹ Hee Tae Yu, MD;¹ Tae-Hoon Kim, MD;¹ Hui-Nam Pak, MD;¹ Moon-Hyoung Lee, MD;¹ Boyoung Joung, MD, PhD^1
1Division of Cardiology, Department of Internal Medicine, Severance Hospital, Yonsei University, Seoul, Republic of Korea ²Department of Cardiology, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea ³Department of Biomedical Informatics, Yonsei University, Seoul, Republic of Korea