Young Joon Lee
Yonsei University · 医学
研究室紹介
Professor Young Joon Lee's research lab focuses on biomedical imaging, molecular diagnostics, and advanced medical technologies, with a strong emphasis on improving cancer detection and treatment through innovative imaging techniques and molecular analysis. The lab investigates the application of advanced imaging modalities such as CT, MRI, and ultrasound in oncology, particularly in prostate and gastric cancers, while also exploring novel diagnostic tools like deep learning algorithms and sentinel node biopsies. Research spans from preclinical studies to clinical translation, aiming to enhance diagnostic accuracy and surgical outcomes.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Abstract The influence of initial pH of the culture medium on hydrogen production was studied using sucrose solution and a mixed microbial flora from a soybean‐meal silo. Hydrogen production was not observed at pH values of 3.0, 11.0 and 12.0 but low production was observed at pH values 5.0 and 5.5. The pH of the experimental mixture decreased rapidly and produced hydrogen gas within 30 h. Methane was not detected at initial pH values between 6.0 and 10.0. The sucrose degradation efficiency incr
Portal phase contrast-enhanced CT scans correlate well with liver IRE ablation size and shape on histopathology.
The clinical application of sentinel node biopsies in early gastric cancer is still controversial even though it appears promising. This study was conducted as a prerequisite quality control for surgical standardization of laparoscopic sentinel basin dissection (SBD) prior to the initiation of a phase III trial.Laparoscopic SBD was performed in patients with preoperative stage T1-2N0 and tumor size <4 cm in diameter. Intraoperative endoscopic submucosal injection of a standardized dual tracer wa
A commercial MRI-based deep learning algorithm for prostate cancer detection showed greater positive predictive value, despite its lower sensitivity, potentially allowing it to assist radiologists in biopsy planning.
The effect of organic modifiers on the separation of a number of closely related isomeric benzoic acids by capillary electrophoresis is described. It is shown that while a single modifier concentration cannot help resolve the entire electropherogram, organic modifiers do significantly enhance the resolution of parts of the separation system by comparison with 40 mmol l–1 phosphate buffer. The effects on separation and retention times are discussed in terms of the effects on electroosmotic flow a
The CT and MR appearance of transitional cell tumors varied according to tumor type. Benign Brenner tumors were homogeneous solid or unilocular cystic pattern, and malignant tumors were heterogeneous solid or multilocular cystic.
We quantify the Monetary Policy Board minutes of the Bank of Korea (BOK) by using text mining. We propose a novel approach that uses a field-specific Korean dictionary and contiguous sequences of words (n-grams) to capture the subtlety of central bank communications. Our text-based indicator helps explain the current and future BOK monetary policy decisions when considering an augmented Taylor rule, suggesting that it contains additional information beyond the currently available macroeconomic v
본 논문은 최근 급격하게 발달하고 있는 텍스트 마이닝 기법의 두 가지, 토픽모델링과 감성분석을 통하여 금융통화위원회의 의사록의 텍스트 데이터에 존재하는 추가적인 정보 유무에 대한 검증을 수행하였다. 금융통화위원회의 의사록은 중앙은행의 소통 강화의 일환으로 공개가 되고 있으며, 이를 공개함으로써 시장참여자들이 올바른 기대를 형성하는데 도움을 줄 수 있을 것이라고 판단하고 있다. 의사록 전체에 대한 토픽모델링 분석결과 총 5개의 토픽을 뽑아내었으며 단어들의 비중을 감안하여 경기, 통화정책, 금융시장, 물가, 부채의 이름으로 명명하였다. 감성분석 기법을 이용하여 각 토픽들의 감성점수를 산출하였고 이를 테일러 준칙에 추가적인 설명 요인으로 포함시켜 중앙은행의 금리 의사결정을 분석하였다. 순서형 프로빗 모형으로 분석한 결과 통화정책, 물가 및 부채토픽의 감성점수는 현재의 금리 의사결정에 추가적인 정보를 제공하는 것으로 나타났으며, 경기토픽의 감성점수는 미래의 금리 의사결정에 대한 예측력을 가