Medical Image Deep Learning with Hospital PACS Dataset. - Junghwan Cho; Kyewook Lee; Ellie Shin; Garry Choy; Synho Do (CoRR, 2015)

Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models. - Junghwan Cho; Ki-Su Park; Manohar Karki; Eunmi Lee; Seokhwan Ko; Jong Kun Kim; Dongeun Lee 004; Jaeyoung Choe; Jeongwoo Son; Myungsoo Kim; Sukhee Lee; Jeongho Lee; et al. (J. Digit. Imaging, 2019)

CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings. - Manohar Karki; Junghwan Cho; Eunmi Lee; Myong-Hun Hahm; Sang-Youl Yoon; Myungsoo Kim; Jae-Yun Ahn; Jeongwoo Son; Shin-Hyung Park; Ki-Hong Kim; Sinyoul Park (Artif. Intell. Medicine, 2020)

Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images. - Manohar Karki; Junghwan Cho (CoRR, 2020)

Interpretable pap smear cell representation for cervical cancer screening. - Yu Ando; Nora Jee-Young Park; Gun Oh Chong; Seokhwan Ko; Donghyeon Lee; Junghwan Cho; Hyungsoo Han (CoRR, 2023)

Prototypical Few-Shot Learning for Histopathology Classification: Leveraging Foundation Models With Adapter Architectures. - Kazi Rakib Hasan; Sijin Kim; Junghwan Cho; Hyung Soo Han (IEEE Access, 2025)

A cluster attention-based multiple instance learning network for enhancing histopathological image interpretation. - Seokhwan Ko; Yu Ando; Moonsik Kim; Nora Jee-Young Park; Hyungsoo Han; Ji Young Park; Junghwan Cho (Comput. Biol. Medicine, 2025)