Yesul Bae
Sungkyunkwan University · 医学
研究室紹介
Professor Yesul Bae's research lab specializes in digital health innovation, focusing on leveraging information and communications technology (ICT), artificial intelligence, and blockchain to enhance healthcare delivery and patient outcomes. The lab develops intelligent systems for remote patient monitoring, digital health literacy assessment, and mental health prediction using natural language processing. It also explores the integration of electronic health records with advanced data analytics to support precision medicine and health information exchange with strong privacy safeguards.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15BACKGROUND: South Korea took preemptive action against coronavirus disease (COVID-19) by implementing extensive testing, thorough epidemiological investigation, strict social distancing, and rapid treatment of patients according to disease severity. The Korean government entrusted large-scale hospitals with the operation of living and treatment support centers (LTSCs) for the management for clinically healthy COVID-19 patients. OBJECTIVE: The aim of this paper is to introduce our experience impl
Background Depression and suicide are critical social problems worldwide, but tools to objectively diagnose them are lacking. Therefore, this study aimed to diagnose depression through machine learning and determine whether it is possible to identify groups at high risk of suicide through words spoken by the participants in a semi-structured interview. Methods A total of 83 healthy and 83 depressed patients were recruited. All participants were recorded during the Mini-International Neuropsychia
BACKGROUND: New health care services such as smart health care and digital therapeutics have greatly expanded. To effectively use these services, digital health literacy skills, involving the use of digital devices to explore and understand health information, are important. Older adults, requiring consistent health management highlight the need for enhanced digital health literacy skills. To address this issue, it is imperative to develop methods to assess older adults' digital health literacy
Background The combined effect of transitions of metabolic health and weight on cardiovascular disease (CVD) remains unclear. We aimed to examine the association of concurrent changes of metabolic health and weight on CVD over time. Methods and Results The study population consisted of 205 394 from the Korean National Health Insurance Service. Metabolic health was determined by fasting serum glucose, total cholesterol, and blood pressure levels, while obesity was determined by body mass index. A
Health information exchange can improve health outcomes and reduce unnecessary medical expenses. An important task in health information exchange is to prove data integrity and strengthen the right to self-determination of individuals. This can be addressed using blockchain technology and dynamic consents. We aimed to develop a blockchain-based mobile platform called HealthPocket to exchange reliable health information with proven integrity through a dynamic consent system based on the HL7 FHIR
Smoking is an important variable for clinical research, but there are few studies regarding automatic obtainment of smoking classification from unstructured bilingual electronic health records (EHR). We aim to develop an algorithm to classify smoking status based on unstructured EHRs using natural language processing (NLP). With acronym replacement and Python package Soynlp, we normalize 4711 bilingual clinical notes. Each EHR notes was classified into 4 categories: current smokers, past smokers
BACKGROUND: Digital health care is an important strategy in the war against COVID-19. South Korea introduced living and treatment support centers (LTSCs) to control regional outbreaks and care for patients with asymptomatic or mild COVID-19. Seoul National University Hospital (SNUH) introduced information and communications technology (ICT)-based solutions to manage clinically healthy patients with COVID-19. OBJECTIVE: This study aims to investigate satisfaction and usability by patients and hea
The concept of MyData emerged as a paradigm shift in personal data management and the process of seeking to transform the current organization-centered system. MyData enables the utilization of one’s own personal information that is scattered among various institutions as a system for data subjects to exercise rights of self-determination. We aimed to develop and demonstrate a MyData platform (MyHealthData) that allows data subjects to download and manage health-related personal data stored in v
Background: The prevalence of nonalcoholic fatty liver disease (NAFLD) has been increasing in the general population. This study evaluated the association between NAFLD and significant coronary stenosis in asymptomatic adults and evaluated sex-based differences. Methods: We performed a retrospective cross-sectional study in participants without previous cardiovascular diseases who visited the Seoul National University Hospital Health Promotion Center for a health checkup between January 1, 2010,
Introduction: To effectively manage patients with coronavirus disease 2019 (COVID-19) while minimizing contact between medical staff, clinical trial protocol that facilitates contactless patient management was designed to predict deterioration of disease condition and monitor mental health status. Methods: Through consultation with infectious disease specialists and psychiatrists, this study identified main clinical indicators related to respiratory and non-respiratory outcomes, and mental healt
Osteoporosis is a medical condition of global concern, with increasing incidence in both sexes. Bone mineral density (BMD), a highly heritable trait, has been proven a useful diagnostic factor in predicting fracture. Because medical information is lacking about male osteoporotic genetics, we conducted a genome-wide association study of BMD in Korean men. With 1,176 participants, we analyzed 4,414,664 single nucleotide polymorphisms (SNPs) after genomic imputation, and identified five SNPs and th