Hwiyoung Kim
연세대학교 의과대학 · 의학
Hwiyoung Kim 교수의 연구실은 의료 영상 분석과 인공지능 기반 진단 보조 시스템 개발을 핵심으로 하며, 특히 3D 생체 구조물(예: 옹포이드)의 정밀 세그멘테이션과 흉부 레이저 영상에서의 결절 탐지에 초점을 맞추고 있습니다. 또한 임상 현장에서의 안정성과 신뢰성을 확보하기 위해 적대적 공격에 대한 내성 강화 및 해석 가능한 머신러닝 모델을 활용한 부모 스트레스 예측 모델링도 진행 중입니다. 연구는 의료 영상의 정밀도 향상과 임상 의사결정 지원을 목표로 하며, 실용적이고 안정적인 AI 기반 진단 시스템의 구현을 추구합니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Contrary to 2D cells, 3D organoid structures are composed of diverse cell types and exhibit morphologies of various sizes. Although researchers frequently monitor morphological changes, analyzing every structure with the naked eye is difficult. Given that deep learning (DL) has been used for 2D cell image segmentation, a trained DL model may assist researchers in organoid image recognition and analysis. In this study, we developed OrgaExtractor, an easy-to-use DL model based on multi-scale U-Net
Due to rapid developments in the deep learning model, artificial intelligence (AI) models are expected to enhance clinical diagnostic ability and work efficiency by assisting physicians. Therefore, many hospitals and private companies are competing to develop AI-based automatic diagnostic systems using medical images. In the near future, many deep learning-based automatic diagnostic systems would be used clinically. However, the possibility of adversarial attacks exploiting certain vulnerabiliti
This decision analytical modeling study found that the DLBS model was more sensitive to detecting pulmonary nodules on chest radiographs compared with the original model. These findings suggest that the DLBS model could be beneficial to radiologists in the detection of lung nodules in chest radiographs without need of the specialized equipment or increase of radiation dose.
By using explainable machine learning models (XGBoost and RF), we investigated major predictors for each subscale of the parenting stress index in caregivers of ASD patients. Identified predictors for parenting stress in this population might help alert clinicians whether a caregiver is at a high risk of experiencing severe parenting stress and if so, providing timely interventions, which could eventually improve the treatment outcome for ASD patients.
Category: Ankle, Ankle Arthritis Introduction/Purpose: The Takakura staging system has been used for the stratification in ankle osteoarthritis(OA). Patient’s OA stage is determined by visual examination on the status of talar and distal tibia in anteroposterior ankle radiograph. Clinical decisions about whether to treat conservatively or to treat with operation such as supra-malleolar osteotomy or arthroplasty may depend on this grading system. However, this is not completely reproducible betwe
