A Deep Learning Method for Intraoperative Age-agnostic and Disease-specific Cardiac Output Monitoring from Arterial Blood Pressure. - Hyun-Lim Yang; Hyung-Chul Lee; Chul-Woo Jung; Min-Soo Kim 002 (BIBE, 2020)

A Real-Time Depth of Anesthesia Monitoring System Based on Deep Neural Network With Large EDO Tolerant EEG Analog Front-End. - Yongjae Park; Su-Hyun Han 001; Wooseok Byun; Ji-Hoon Kim 003; Hyung-Chul Lee; Seong-Jin Kim (IEEE Trans. Biomed. Circuits Syst., 2020)

Attention Mechanisms for Physiological Signal Deep Learning: Which Attention Should We Take? - Seong-A. Park; Hyung-Chul Lee; Chul-Woo Jung; Hyun-Lim Yang (MICCAI (1), 2022)

Developing and Validating Multi-Modal Models for Mortality Prediction in COVID-19 Patients: a Multi-center Retrospective Study. - Joy Tzung-yu Wu; Miguel Ángel Armengol de La Hoz; Po-Chih Kuo; Joseph Alexander Paguio; Jasper Seth Yao; Edward Christopher Dee; Wesley Yeung; Jerry Jurado; Achintya Moulick; Carmelo Milazzo; Paloma Peinado; Paula Villares; et al. (J. Digit. Imaging, 2022)

Multi-center validation of machine learning model for preoperative prediction of postoperative mortality. - Seung Wook Lee; Hyung-Chul Lee; Jungyo Suh; Kyung Hyun Lee; Heonyi Lee; Suryang Seo; Tae Kyong Kim; Sang-Wook Lee; Yi-Jun Kim (npj Digit. Medicine, 2022)

Development and validation of a reinforcement learning model for ventilation control during emergence from general anesthesia. - Hyeonhoon Lee; Hyun-Kyu Yoon; Jaewon Kim; Ji Soo Park; Chang-Hoon Koo; Dongwook Won; Hyung-Chul Lee (npj Digit. Medicine, 2023)

Real-time machine learning model to predict in-hospital cardiac arrest using heart rate variability in ICU. - Hyeonhoon Lee; Hyun-Lim Yang; Ho Geol Ryu; Chul-Woo Jung; Youn Joung Cho; Soo Bin Yoon; Hyun-Kyu Yoon; Hyung-Chul Lee (npj Digit. Medicine, 2023)

Deep reinforcement learning-based propofol infusion control for anesthesia: A feasibility study with a 3000-subject dataset. - Won Joon Yun; Myungjae Shin; Soyi Jung; JeongGil Ko; Hyung-Chul Lee; Joongheon Kim (Comput. Biol. Medicine, 2023)

Automatic segmentation of atrial fibrillation and flutter in single-lead electrocardiograms by self-supervised learning and Transformer architecture. - Donghwan Yun; Hyun-Lim Yang; Soonil Kwon; So-Ryoung Lee; Kyungju Kim; Kwangsoo Kim; Hyung-Chul Lee; Chul-Woo Jung; Yon Su Kim; Seung Seok Han (J. Am. Medical Informatics Assoc., 2023)

Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health. - Mira Moukheiber; Lama Moukheiber; Dana Moukheiber; Hyung-Chul Lee (IJCAI, 2024)

NSTRI Global Collaborative Research Data Platform. - Hyeonhoon Lee; Hanseul Kim; Kyungmin Cho; Hyung-Chul Lee (CoRR, 2024)

Non-invasive prediction of massive transfusion during surgery using intraoperative hemodynamic monitoring data. - Doyun Kwon; Young Mi Jung; Hyung-Chul Lee; Tae Kyong Kim; Kwangsoo Kim; Garam Lee; Dokyoon Kim; Seung-Bo Lee; Seung Mi Lee (J. Biomed. Informatics, 2024)

Reinforcement learning model for optimizing dexmedetomidine dosing to prevent delirium in critically ill patients. - Hong Yeul Lee; Soomin Chung; Dongwoo Hyeon; Hyun-Lim Yang; Hyung-Chul Lee; Ho Geol Ryu; Hyeonhoon Lee (npj Digit. Medicine, 2024)

Comparison of NLP machine learning models with human physicians for ASA Physical Status classification. - Soo Bin Yoon; Jipyeong Lee; Hyung-Chul Lee; Chul-Woo Jung; Hyeonhoon Lee (npj Digit. Medicine, 2024)

EchoQA: A Large Collection of Instruction Tuning Data for Echocardiogram Reports. - Lama Moukheiber; Mira Moukheiber; Dana Moukheiiber; Jae-Woo Ju; Hyung-Chul Lee (CoRR, 2025)