E. Urtnasan

发表

Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG

Kyoung-Joung Lee, E. Joo, E. Urtnasan, 2020, Journal of Korean medical science.

Automatic Detection Algorithm for Snoring and Heart beat Using a Single Piezoelectric Sensor

Kyoung-Joung Lee, E. Urtnasan, P. Jeong, 2015 .

Sleep Apnea Detection Using a Piezo Snoring Sensor: A Pilot study

Hyo-Ki Lee, Erdenebayar Urtnasan, Kyoung-Joung Lee, 2014 .

Deep Convolutional Recurrent Model for Automatic Scoring Sleep Stages Based on Single-Lead ECG Signal

Kyoung-Joung Lee, E. Joo, E. Urtnasan, 2022, Diagnostics.

Noninvasive Screening Tool for Hyperkalemia Using a Single-Lead Electrocardiogram and Deep Learning: Development and Usability Study

H. Youk, H. Lee, E. Urtnasan, 2022, JMIR medical informatics.

Concept and Proof of the Lifelog Bigdata Platform for Digital Healthcare and Precision Medicine on the Cloud

H. Youk, H. Lee, E. Urtnasan, 2022, Yonsei medical journal.

Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram

Erdenebayar Urtnasan, Jonguk Park, Kyoung-Joung Lee, 2019, Comput. Methods Programs Biomed..

Optimal Classifier for Detection of Obstructive Sleep Apnea Using a Heartbeat Signal

Kyoung-Joung Lee, Sooyong Lee, Erdenebayar Urtnasan, 2017, Int. J. Fuzzy Log. Intell. Syst..

A Prediction Model of Incident Cardiovascular Disease in Patients with Sleep-Disordered Breathing

Kyoung-Joung Lee, E. Urtnasan, Jonguk Park, 2021, Diagnostics.

Automatic classification of apnea/hypopnea events through sleep/wake states and severity of SDB from a pulse oximeter

Hyo-Ki Lee, Erdenebayar Urtnasan, Kyoung-Joung Lee, 2015, Physiological measurement.

Automatic detection of sleep-disordered breathing events using recurrent neural networks from an electrocardiogram signal

Kyoung-Joung Lee, Jong-Uk Park, Erdenebayar Urtnasan, 2018, Neural Computing and Applications.

Multiclass classification of obstructive sleep apnea/hypopnea based on a convolutional neural network from a single-lead electrocardiogram

Kyoung-Joung Lee, Jong-Uk Park, Erdenebayar Urtnasan, 2018, Physiological measurement.

Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network

Kyoung-Joung Lee, Erdenebayar Urtnasan, Jonguk Park, 2018, Journal of Medical Systems.

Automatic Classification of Sleep Stage from an ECG Signal Using a Gated-Recurrent Unit

Erdenebayar Urtnasan, Sooyong Lee, Kyoung-Joung Lee, 2020, Int. J. Fuzzy Log. Intell. Syst..

Deep Learning for Automatic Detection of Periodic Limb Movement Disorder Based on Electrocardiogram Signals

Kyoung-Joung Lee, E. Urtnasan, Jonguk Park, 2022, Diagnostics.

AI-Enabled Algorithm for Automatic Classification of Sleep Disorders Based on Single-Lead Electrocardiogram

E. Joo, E. Urtnasan, K. Lee, 2021, Diagnostics.

AI-Enabled Algorithm for Automatic Classification of Sleep Disorders Based on Single-Lead Electrocardiogram

E. Joo, E. Urtnasan, K. Lee, 2021, Diagnostics.

Prediction Method of Periodic Limb Movements Based on Deep Learning Using ECG Signal

Erdenebayar Urtnasan, Jonguk Park, Sooyong Lee, 2020, Int. J. Fuzzy Log. Intell. Syst..

A Prediction Algorithm for Hypoglycemia Based on Support Vector Machine Using Glucose Level and Electrocardiogram

E. Urtnasan, Jonguk Park, Yerin Lee, 2022, Journal of medical systems.

AI-based Prediction Model for Incident of Obstructive Sleep Apnea Using ECG Signals: Utilization of MrOS

E. Urtnasan, S. Koh, Sangwon Hwang, 2023, Digital Health Research.

Developing prediction algorithms for late-life depression using wearable devices: a cohort study protocol

E. Urtnasan, Sangwon Hwang, Jin-kyung Lee, 2024, BMJ open.