Paeng, Kyunghyun

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

Bandi, P., Geessink, O., Manson, Q., Van Dijk, M., Balkenhol, M., Hermsen, M., Ehteshami Bejnordi, B., Lee, B., Paeng, K., Zhong, A., et al. (2019) · IEEE Transactions on Medical Imaging

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 569

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as complementary biomarker for immune checkpoint inhibition in non-small-cell lung cancer

Park, S., Ock, C.-Y., Kim, H., Pereira, S., Park, S., Ma, M., Choi, S., Kim, S., Shin, S., Aum, B. J., et al. (2022) · Journal of Clinical Oncology

Cancer Immunotherapy and BiomarkersAI in cancer detection

Cited by 280

Artificial intelligence (AI)–powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC)

Lee, H. J., Cho, S. Y., Cho, E. Y., Lim, Y., Cho, S. I., Jung, W., Song, S., Kang, M., Ryu, J., Ma, M., et al. (2022) · Journal of Clinical Oncology

Breast Cancer Treatment StudiesAI in cancer detection

Cited by 10