공성혜 교수

Background: 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). Methods: 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 months). Results: The mean ages

ABSTRACT 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 (1

BACKGROUND: Although recent studies comparing various dosages and intervals of vitamin D supplementation have been published, it is yet to be elucidated whether there is an appropriate dose or interval to provide benefit regarding fracture risk. We aimed to assess the published evidence available to date regarding the putative beneficial effects of vitamin D supplements on fractures and falls according to various dosages and intervals. METHODS: We performed a meta-analysis of randomized controll

BACKGRUOUND: Since image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data. METHODS: This study included 1,595 participants aged 50 to 75 years with at least two lumbosacral radiographs without baseline fractures from 2010 to 2015 at Seoul National University Hospital. Positive and negative cases were defined according to whether vertebral fractures developed during follow-up.

We evaluated whether metabolic factors were associated with cognitive decline, compared to baseline cognitive function, among geriatric population. The present study evaluated data from an ongoing prospective community-based Korean cohort study. Among 1,387 participants who were >65 years old, 422 participants were evaluated using the Korean mini-mental status examination (K-MMSE) at the baseline and follow-up examinations. The mean age at the baseline was 69.3 ± 2.9 years, and 222 participants

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

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

OBJECTIVE: Diagnosing parathyroid carcinoma (PC) is complicated and controversial that early diagnosis and intervention are often difficult. Therefore, we aimed to elucidate the protein signatures of PC through quantitative proteomic analyses to aid in the early and accurate diagnosis of PC. DESIGN: We conducted a retrospective cohort study. METHODS: We performed liquid chromatography with tandem mass spectrometry using formalin-fixed paraffin-embedded samples. For the analyses, 23 PC and 15 par