148 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR5 papers
- Hankuk University of Foreign StudiesKR3 papers
- Korea Advanced Institute of Science and TechnologyKR2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- Centro de Investigaciones Energéticas, Medioambientales y TecnológicasES1 paper
- Chungbuk National UniversityKR1 paper
- European Organization for Nuclear ResearchCH1 paper
- Ghent UniversityBE1 paper
- Institut de Physique des 2 Infinis de LyonFR1 paper
- Kyushu UniversityJP1 paper
- Laboratoire de Physique des 2 Infinis Irène Joliot-CurieFR1 paper
- Lyon 1 UniversitéFR1 paper
12 papers
Cross-Model Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Across Three Large Language Models
Kihyuk Lee
This study compared repeated generation consistency of exercise prescription outputs across three large language models (LLMs), specifically GPT-4.1, Claude Sonnet 4.6, and Gemini…
"I Choose to Live, for Life Itself": Understanding Agency of Home-Based Care Patients Through Information Practices and Relational Dynamics in Care Networks
Sung-In Kim, Joonyoung Park, Bogoan Kim +1
Home-based care (HBC) delivers medical and care services in patients' living environments, offering unique opportunities for patient-centered care. However, patient agency is often…
Bidirectional GaitNet: A Bidirectional Prediction Model of Human Gait and Anatomical Conditions
Jungnam Park, Moon Seok Park, Jehee Lee +1
We present a novel generative model, called Bidirectional GaitNet, that learns the relationship between human anatomy and its gait. The simulation model of human anatomy is a compr…
Description and stability of a RPC-based calorimeter in electromagnetic and hadronic shower environments
D. Boumediene, V. Francais, J. Apostolakis +36
The CALICE Semi-Digital Hadron Calorimeter technological prototype completed in 2011 is a sampling calorimeter using Glass Resistive Plate Chamber (GRPC) detectors as the active me…
Machine Learning-Based COVID-19 Patients Triage Algorithm using Patient-Generated Health Data from Nationwide Multicenter Database
Min Sue Park, Hyeontae Jo, Haeun Lee +2
A prompt severity assessment model of patients confirmed for having infectious diseases could enable efficient diagnosis while alleviating burden on the medical system. This study…
Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGAN
Gyutaek Oh, Byeongsu Sim, Hyungjin Chung +2
Recently, deep learning approaches for accelerated MRI have been extensively studied thanks to their high performance reconstruction in spite of significantly reduced runtime compl…
Functionality-Driven Musculature Retargeting
Hoseok Ryu, Minseok Kim, Seunghwan Lee +3
We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and…
The CNN-based Coronary Occlusion Site Localization with Effective Preprocessing Method
YeongHyeon Park, Il Dong Yun, Si-Hyuck Kang
The Coronary Artery Occlusion (CAO) acutely comes to human, and it highly threats the human's life. When CAO detected, Percutaneous Coronary Intervention (PCI) should be conducted…
Reinforcement Learning-based Automatic Diagnosis of Acute Appendicitis in Abdominal CT
Walid Abdullah Al, Il Dong Yun, Kyong Joon Lee
Acute appendicitis characterized by a painful inflammation of the vermiform appendix is one of the most common surgical emergencies. Localizing the appendix is challenging due to i…
Classification of Findings with Localized Lesions in Fundoscopic Images using a Regionally Guided CNN
Jaemin Son, Woong Bae, Sangkeun Kim +2
Fundoscopic images are often investigated by ophthalmologists to spot abnormal lesions to make diagnoses. Recent successes of convolutional neural networks are confined to diagnose…
Highrisk Prediction from Electronic Medical Records via Deep Attention Networks
You Jin Kim, Yun-Geun Lee, Jeong Whun Kim +3
Predicting highrisk vascular diseases is a significant issue in the medical domain. Most predicting methods predict the prognosis of patients from pathological and radiological mea…
Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images
Seung Yeon Shin, Soochahn Lee, Il Dong Yun +2
We propose a framework for localization and classification of masses in breast ultrasound (BUS) images. We have experimentally found that training convolutional neural network base…