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Korean Journal of Pathology|January 15, 2014
Cytomorphological findings and histological correlation of low-grade cribriform cystadenocarcinoma of salivary gland in fine-needle aspiration: a case studyYoung Sin Ko, Ja Seung Koo
Studies in Health Technology and Informatics|August 23, 2024
Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology ImagingSuk Min Ha, Young Sin Ko, Youngjin Park
Studies in Health Technology and Informatics|May 17, 2025
Understanding Stain Separation Improves Cross-Scanner Adenocarcinoma Segmentation with Joint Multi-Task LearningHo Heon Kim, Won Chan Jeong, Youngjin Park, et al.
JMIR Medical Informatics|February 4, 2026
Ranking-Aware Multiple Instance Learning for Histopathology Slide Classification: Development and Validation StudyHo Heon Kim, Gisu Hwang, Won Chan Jeong, et al.
Diagnostics (Basel, Switzerland)|June 24, 2022
MixPatch: A New Method for Training Histopathology Image ClassifiersYoungjin Park, Mujin Kim, Murtaza Ashraf, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|October 31, 2024
WISE: Efficient WSI selection for active learning in histopathologyHyeongu Kang, Mujin Kim, Young Sin Ko, et al.
BMC Medical Imaging|July 2, 2025
Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networksSakonporn Noree, Willmer Rafell Quinones Robles, Young Sin Ko, et al.
Journal of Pathology Informatics|October 28, 2025
Evaluating the robustness of slide-level AI predictions on out-of-focus whole slide images: A retrospective observational studyHo Heon Kim, Young Sin Ko, Won Chan Jeong, et al.
Scientific Reports|January 27, 2022
A loss-based patch label denoising method for improving whole-slide image analysis using a convolutional neural networkMurtaza Ashraf, Willmer Rafell Quiñones Robles, Mujin Kim, et al.
BMC Medical Imaging|January 3, 2024
A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplaceMujin Kim, Willmer Rafell Quiñones Robles, Young Sin Ko, et al.
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