Sirinukunwattana, Korsuk

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 3,293

Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images

Sirinukunwattana, K., Raza, S. E. A., Tsang, Y.-W., Snead, D. R. J., Cree, I. A., & Rajpoot, N. M. (2016) · IEEE Transactions on Medical Imaging

AI in cancer detectionCell Image Analysis Techniques

Cited by 1,224

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

Sirinukunwattana, K., Domingo, E., Richman, S. D., Redmond, K. L., Blake, A., Verrill, C., Leedham, S. J., Chatzipli, A., Hardy, C., Whalley, C. M., et al. (2021) · Gut

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 264

Digital Pathology: 15th European Congress, ECDP 2019, Warwick, UK, April 10–13, 2019, Proceedings

Bankhead, P., Janowczyk, A. R., Reyes‐Aldasoro, C. C., Sirinukunwattana, K., Veta, M., Reyes-Aldasoro, C. C., Veta, M., Janowczyk, A., Bankhead, P., & Sirinukunwattana, K. (2019) · Lecture Notes in Computer Science

AI in cancer detectionCell Image Analysis Techniques

Cited by 9