Snead, David

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

Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study

Bilal, M., Raza, S. E. A., Azam, A., Graham, S., Ilyas, M., Cree, I. A., Snead, D., Minhas, F., & Rajpoot, N. M. (2021) · The Lancet Digital Health

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 299

Validation of digital pathology imaging for primary histopathological diagnosis

Snead, D. R. J., Tsang, Y., Meskiri, A., Kimani, P. K., Crossman, R., Rajpoot, N. M., Blessing, E., Chen, K., Gopalakrishnan, K., Matthews, P., et al. (2016) · Histopathology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 238

Context-aware convolutional neural network for grading of colorectal cancer histology images

Shaban, M., Awan, R., Fraz, M. M., Azam, A., Tsang, Y.-W., Snead, D., & Rajpoot, N. M. (2020) · IEEE Transactions on Medical Imaging

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 179