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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.

딥러닝유전체 시퀀싱전기생리 신호 분석병리 영상 분석정밀의료

연구 현황

논문 수
157
총 인용 수
806
최근 5년 논문
50
주요 분야
컴퓨터과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
50총합
2022
2023
2024
2025
2026
5개년 연도별 피인용 수
305총합
20222023202420252026

주요 논문

15
1
논문|인용수 143·2016
Comparison between Saliva and Nasopharyngeal Swab Specimens for Detection of Respiratory Viruses by Multiplex Reverse Transcription-PCR
Young‐Gon Kim, Seung Gyu Yun, Min Young Kim, Kwisung Park, Chi Hyun Cho, Soo Young Yoon, Myung‐Hyun Nam, Chang Kyu Lee, Yunjung Cho, Chae Seung Lim
SJR Q1FWCI 2.1Journal of Clinical MicrobiologyOA

Nasopharyngeal 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

EpidemiologyMedicine
2
논문|인용수 71·2022
Predicting Parkinson's disease using gradient boosting decision tree models with electroencephalography signals
Seung-Bo Lee, Yong-Jeong Kim, Sungeun Hwang, Hyoshin Son, Sang Kun Lee, Kyung‐Il Park, Young-Gon Kim
SJR Q1FWCI 8.6Parkinsonism & Related Disorders
NeurologyMedicine
3
논문|인용수 63·2020
Effectiveness of transfer learning for enhancing tumor classification with a convolutional neural network on frozen sections
Young‐Gon Kim, Sungchul Kim, Cristina Eunbee Cho, In Hye Song, Hee Jin Lee, Soomin Ahn, So Yeon Park, Gyungyub Gong, Namkug Kim
SJR Q1FWCI 6.4Scientific ReportsOA

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

Artificial IntelligenceComputer Science
4
논문|인용수 27·2019
A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides
Young‐Gon Kim, Gyuheon Choi, Heounjeong Go, Yongwon Cho, Hyunna Lee, A-Reum Lee, Beomhee Park, Namkug Kim
SJR Q1FWCI 1.7Scientific ReportsOA

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

Computer Vision and Pattern RecognitionComputer Science
5
논문|인용수 16·2012
A design of user authentication system using QR code identifying method
Young‐Gon Kim, Moon-Seog Jun
FWCI 4.0Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
Information SystemsComputer Science
6
논문|인용수 16·2020
SnackVar
Young‐Gon Kim, Man Jin Kim, Hyukmin Lee, Jung Ae Lee, Ji Yun Song, Sung Im Cho, Sung Sup Park, Moon‐Woo Seong
SJR Q1FWCI 0.4Journal of Molecular Diagnostics
Molecular BiologyBiochemistry, Genetics and Molecular Biology
7
논문|인용수 15·2023
Using spectral and temporal filters with EEG signal to predict the temporal lobe epilepsy outcome after antiseizure medication via machine learning
Youmin Shin, Sungeun Hwang, Seung-Bo Lee, Hyoshin Son, Kon Chu, Ki‐Young Jung, Sang Kun Lee, Kyung‐Il Park, Young-Gon Kim
SJR Q1FWCI 2.6Scientific ReportsOA

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

Cognitive NeuroscienceNeuroscience
8
논문|인용수 14·2023
Whole-genome sequencing in clinically diagnosed Charcot–Marie–Tooth disease undiagnosed by whole-exome sequencing
Young‐Gon Kim, Hyemi Kwon, Jong‐Ho Park, Soo Hyun Nam, Changhee Ha, Sunghwan Shin, Won Young Heo, Hye Jin Kim, Ki Wha Chung, Ja‐Hyun Jang, Jong‐Won Kim, Byung‐Ok Choi
SJR Q1FWCI 2.1Brain CommunicationsOA

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

Cellular and Molecular NeuroscienceNeuroscience
9
book chapter|인용수 13·2006
Modified Naïve Bayes Classifier for E-Catalog Classification
Young‐Gon Kim, Taehee Lee, Jonghoon Chun, Sang‐Goo Lee
SJR Q2FWCI 0.9Lecture notes in computer science
Artificial IntelligenceComputer Science
10
논문|인용수 11·2024
A spectrum of nonsense-mediated mRNA decay efficiency along the degree of mutational constraint
Young‐Gon Kim, Hyunju Kang, Beomki Lee, Hyeok-Jae Jang, Jong‐Ho Park, Changhee Ha, Hogun Park, Jong‐Won Kim
SJR Q1FWCI 2.6Communications BiologyOA

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

Molecular BiologyBiochemistry, Genetics and Molecular Biology
11
letter|인용수 9·2021
Rates of Coinfection Between SARS-CoV-2 and Other Respiratory Viruses in Korea
Young‐Gon Kim, Hyunwoong Park, So Yeon Kim, Ki Ho Hong, Man Jin Kim, Hyukmin Lee, Sung Sup Park, Moon‐Woo Seong
SJR Q2FWCI 1.1Annals of Laboratory MedicineOA

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

EpidemiologyMedicine
12
preprint|인용수 8·2020
Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer
Young‐Gon Kim, In Hye Song, Hyunna Lee, Dong Hyun Yang, Namkug Kim, Dongho Shin, Yeonsoo Yoo, Kyowoon Lee, Dahye Kim, Hwejin Jung, Hyunbin Cho, Hyungyu Lee
Research Square (Research Square)OA

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

Artificial IntelligenceComputer Science
13
논문|인용수 8·2021
Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
Jiwoo Lee, Sohyeon Park, Young‐Gon Kim, Eun‐Kyu Lee, Junghee Jo
SJR Q2FWCI 1.7ElectronicsOA

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

Information SystemsComputer Science
14
논문|인용수 7·2023
Enrichment of titin-truncating variants in exon 327 in dilated cardiomyopathy and its relevance to reduced nonsense-mediated mRNA decay efficiency
Young‐Gon Kim, Changhee Ha, Sunghwan Shin, Jong‐Ho Park, Ja‐Hyun Jang, Jong‐Won Kim
SJR Q2FWCI 1.5Frontiers in GeneticsOA

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

Cardiology and Cardiovascular MedicineMedicine
15
논문|인용수 6·2021
SnackNTM: An Open-Source Software for Sanger Sequencing-based Identification of Nontuberculous Mycobacterial Species
Young‐Gon Kim, Kiwook Jung, Seunghwan Kim, Man Jin Kim, Jee-Soo Lee, Sung Sup Park, Moon‐Woo Seong
SJR Q2FWCI 0.6Annals of Laboratory MedicineOA

SnackNTM is expected to reduce the workload for NTM identification, especially in clinical laboratories that process large numbers of cases.

EpidemiologyMedicine

대표 연구 분야

Information SystemsArtificial IntelligenceAerospace EngineeringSociology and Political ScienceEpidemiologyComputer Vision and Pattern Recognition

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