Sung Hye Kong
서울대학교 의예과 · 의학
성혜공 교수의 연구실은 골다공로시스 및 골절 위험 예측을 중심으로, 영상의학, 생체정보, 임상 데이터를 융합한 인공지능 기반 예측 모델 개발에 주력하고 있습니다. 특히, TBS(세밀한 뼈조직 구조 평가), FRAX와 같은 기존 예측 도구를 넘어 딥러닝 기반 영상 분석 알고리즘(DepthSurv 등)을 활용한 개인 맞춤형 골절 위험 평가에 초점을 맞추고 있습니다. 또한, 비만성 당뇨병 환자나 저위험도의 미세갑상비암성 갑상선암 환자에서의 생존율 및 삶의 질 영향을 분석하며 임상적 의사결정 지원 모델을 개발하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
<b><i>Background:</i></b> In this ongoing multicenter prospective cohort study on active surveillance (AS) in low-risk papillary thyroid microcarcinoma (PTMC), we aimed to compare the quality of life (QoL) of participants based on their choice of treatment, that is, AS or immediate surgery (OP). <b><i>Methods:</i></b> QoL of 203 participants who chose AS and 192 participants who underwent OP was evaluated using a thyroid-specific QoL questionnaire at diagnosis and during follow-up (median 8 mont
The prediction of fracture risk in osteoporotic patients has been a topic of interest for decades, and models have been developed for the accurate prediction of fracture, including the fracture risk assessment tool (FRAX). As machine-learning methodologies have recently emerged as a potential model for medical prediction tools, we aimed to develop a novel fracture prediction model using machine-learning methods in a prospective community-based cohort. In this study, 2227 participants (1257 femal
Daily vitamin D dose of 800 to 1,000 IU was the most probable way to reduce the fracture and fall risk. Further studies designed with various regimens and targeted vitamin D levels are required to elucidate the benefits of vitamin D supplements.
DeepSurv, a CNN-based prediction algorithm using baseline image and clinical information, outperformed the FRAX and CoxPH models in predicting osteoporotic fracture from spine radiographs in a longitudinal cohort.
The trabecular bone score (TBS) was introduced as an indirect index of trabecular microarchitecture, complementary to bone mineral density (BMD), and is derived using the same dual energy X-ray absorptiometry images. Recently, it has been approved for clinical use in Korea. Therefore, we conducted a comprehensive review to optimize the use of TBS in clinical practice. The TBS is an independent predictor of osteoporotic fractures in postmenopausal women and men aged >50 years. The TBS is potentia
In this unprecedented era of the overwhelming volume of medical data, machine learning can be a promising tool that may shed light on an individualized approach and a better understanding of the disease in the field of osteoporosis research, similar to that in other research fields. This review aimed to provide an overview of the latest studies using machine learning to address issues, mainly focusing on osteoporosis and fractures. Machine learning models for diagnosing and classifying osteoporo
Dapagliflozin treatment did not affect systemic endothelial function or renal injury markers except <i>N</i>-acetyl-beta-D-glucosaminidase.
We identified key proteins differentially expressed between PC and PA using proteomic analyses of parathyroid neoplasms. These findings may help to diagnose PC accurately and elucidate potential therapeutic targets.
