김영곤 교수
Yeonggon Kim
서울대학교 · 컴퓨터과학
연구실 소개
김영곤 교수의 연구실은 임상 진단의 정밀도와 효율성을 높이기 위한 첨단 바이오의학 기술 개발에 주력하고 있습니다. 주로 면역조직화학 영상 분석, 유전체 시퀀싱, 전기생리 신호 처리를 기반으로 한 인공지능 기반 진단 보조 시스템을 개발하며, 특히 신장 이식 반응 평가, 림프절 냉동절편 진단, 간질 치료 예측 등 임상적 난이도 높은 문제를 해결하고자 합니다. 병원에서의 실용적 적용을 고려한 정밀의료 기반의 딥러닝 및 분석 알고리즘 개발이 핵심 연구 방향입니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Nasopharyngeal swabs (NPSs) are being widely used as specimens for multiplex real-time reverse transcription (RT)-PCR for respiratory virus detection. However, it remains unclear whether NPS specimens are optimal for all viruses targeted by multiplex RT-PCR. In addition, the procedure to obtain NPS specimens causes coughing in most patients, which possibly increases the risk of nosocomial spread of viruses. In this study, paired NPS and saliva specimens were collected from 236 adult male patient
Fast and accurate confirmation of metastasis on the frozen tissue section of intraoperative sentinel lymph node biopsy is an essential tool for critical surgical decisions. However, accurate diagnosis by pathologists is difficult within the time limitations. Training a robust and accurate deep learning model is also difficult owing to the limited number of frozen datasets with high quality labels. To overcome these issues, we validated the effectiveness of transfer learning from CAMELYON16 to im
Pathologic diagnoses mainly depend on visual scoring by pathologists, a process that can be time-consuming, laborious, and susceptible to inter- and/or intra-observer variations. This study proposes a novel method to enhance pathologic scoring of renal allograft rejection. A fully automated system using a convolutional neural network (CNN) was developed to identify regions of interest (ROIs) and to detect C4d positive and negative peritubular capillaries (PTCs) in giga-pixel immunostained slides
Abstract Epilepsy is a neurological disorder in which the brain is transiently altered . Predicting outcomes in epilepsy is essential for providing feedback that can foster improved outcomes in the future. This study aimed to investigate whether applying spectral and temporal filters to resting-state electroencephalography (EEG) signals could improve the prediction of outcomes for patients taking antiseizure medication to treat temporal lobe epilepsy (TLE). We collected EEG data from a total of
Whole-genome sequencing is the most comprehensive form of next-generation sequencing method. We aimed to assess the additional diagnostic yield of whole-genome sequencing in patients with clinically diagnosed Charcot-Marie-Tooth disease when compared with whole-exome sequencing, which has not been reported in the literature. Whole-genome sequencing was performed on 72 families whose genetic cause of clinically diagnosed Charcot-Marie-Tooth disease was not revealed after the whole-exome sequencin
Despite its importance for regulating gene expression, nonsense-mediated mRNA decay (NMD) remains poorly understood. Here, we extend the findings of a previous landmark study that proposed several factors associated with NMD efficiency using matched genome and transcriptome data from The Cancer Genome Atlas Program (TCGA) by incorporating additional data including Genotype-Tissue Expression (GTEx), gnomAD, and metrics for mutational constraints. Factors affecting NMD efficiency are analyzed usin
Young-gon Kim, M.D., Hyunwoong Park, M.D., Ph.D., So Yeon Kim, M.D., Ph.D., Ki Ho Hong, M.D., Ph.D., Man Jin Kim, M.D., Jee-Soo Lee, M.D., Sung-Sup Park, M.D., Ph.D., and Moon-Woo Seong, M.D., Ph.D.. Ann Lab Med 2022;42:110-2. https://doi.org/10.3343/alm.2022.42.1.110
Abstract Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of sentinel lymph nodes by a pathologist is not easy and is a tedious and time-consuming task. The purpose of this study is to review a challenge competition (HeLP 2018) to develop automated solutions for the classification of metastases in hematoxylin and eosin–stained frozen tissue sections of SLNs in br
The Internet of Things (IoT) technology is rapidly being applied to real life, but the application of a corresponding secure and convenient authentication method is still in significant challenge. So far, pattern, password and fingerprint authentication are the most used methods, but it is important to address various security vulnerabilities and limitations of these approaches. In the case of fingerprint recognition, additional hardware such as a fingerprint scanner is required, which causes co
Titin truncating variants (TTNtvs) are the most common genetic cause of dilated cardiomyopathy (DCM). Among four regions of titin, A-band enrichment of DCM-causing TTNtvs is widely accepted but the underlying mechanism is still unknown. Meanwhile, few reports have identified exon 327 as a highly mutated A-band exon but the degree of exon 327 enrichment has not been quantitatively investigated. To find the real hotspot of DCM-causing TTNtvs, we aimed to reassess the degree of TTNtv enrichment in
SnackNTM is expected to reduce the workload for NTM identification, especially in clinical laboratories that process large numbers of cases.
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