Kyung Hyun Lee

Seoul & Suwon

Republic of Korea

lkh256 [at] gmail [dot] com

AI researcher in physiological and clinical time-series learning

I develop and evaluate machine learning models for physiological signals and longitudinal clinical data. The work began with biosignals — EMG and ECG-derived RR intervals — and moved to electronic health records and repeated clinical measurements. The question that connects them: when data arrive as a sequence, how should a model learn from it, and how should it be evaluated where it will be used — at other hospitals, and read repeatedly as new measurements arrive rather than once per patient? My doctoral work at SAIHST is advised by Professor Byung-Jae Lee.

News

Sep 30, 2026	research Paper accepted at the NeurIPS 2026 Workshop on Responsible Communication of Machine Learning Research in Biomedicine (RCMLR): Median alert lead time tracks how long patients were observed, and runs opposite to specificity. Poster presentation on 12 December 2026, Sydney; also served as a reviewer for the workshop.
Sep 08, 2026	research Presented a poster on spirometry trajectories and incident airflow obstruction at the ERS International Congress 2026, Barcelona — conference notes.
Jul 29, 2026	teaching Appointed lecturer in the Department of Sport Science, University of Seoul, teaching Exercise and Digital Healthcare (Fall 2026).
May 08, 2026	research Published in *npj Digital Medicine*: multi-center external validation of deep learning AKI prediction models under simulated continuous monitoring — paper.
Mar 30, 2026	research Presented an oral poster on online-simulation evaluation of AKI prediction models at AKI & CRRT 2026, San Diego — conference notes.

Selected Publications

Acute & Critical Care Machine Learning Clinical Research Evaluation Framework

Deep learning models for acute kidney injury prediction: multi-center external validation and evaluation under simulated continuous monitoring conditions

Kyung Hyun Lee^†, Donghwee Yoon^†, Hyunsun Lim, and 2 more authors

npj Digital Medicine, May 2026

DOI
Acute & Critical Care Machine Learning Clinical Research

Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study

Ji-Hyun Kim^†, Kyung Hyun Lee^†, Kwang Joon Kim, and 11 more authors

BMJ Health & Care Informatics, 2025

DOI
Biosignals Machine Learning Clinical Research

Deep learning-based stress detection from RR intervals in major depressive disorder, panic disorder, and healthy individuals

Kyung Hyun Lee^†, Chul-Hyun Cho^†, Ah Young Kim, and 2 more authors

Frontiers in Psychiatry, 2025

DOI Code
Respiratory Medicine Machine Learning Clinical Research

Novel artificial intelligence-based technology to diagnose asthma using methacholine challenge tests

Noeul Kang^†, Kyung Hyun Lee^†, Sangwon Byun, and 3 more authors

Allergy, Asthma & Immunology Research, 2024

DOI Code
Biosignals Machine Learning

Age prediction in healthy subjects using RR intervals and heart rate variability: A pilot study based on deep learning

Kyung Hyun Lee^† and Sangwon Byun^*

Applied Sciences, 2023

DOI Code
Biosignals Machine Learning

Electromyogram-based classification of hand and finger gestures using artificial neural networks

Kyung Hyun Lee^†, Ji Young Min^†, and Sangwon Byun^*

Sensors, 2022

DOI Code

All publications →

Current Research

Longitudinal pulmonary function Doctoral research on reading repeated screening spirometry as a trajectory to anticipate airflow obstruction. Presented at the ERS International Congress 2026; not yet published.
Evaluating continuously read clinical models Minute-level intraoperative hypotension monitoring and multicenter cardiac arrest prediction. Manuscripts under review; one preprint.

Beyond Research

I contributed to a cardiac arrest early-warning system at AITRICS that was approved by Korea's MFDS as an AI medical device, and I now lead product development of the AKI model toward the same approval. In 2025 I co-founded BreathYou, a respiratory and allergy AI startup incorporated as BreathYou Co., Ltd. in August 2026. I also teach Exercise and Digital Healthcare at the University of Seoul.