Zörnig, Inka

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

Kather, J. N., Krisam, J., Charoentong, P., Luedde, T., Herpel, E., Weis, C.-A., Gaiser, T., Marx, A., Valous, N. A., Ferber, D., et al. (2019) · PLOS Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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Key parameters of tumor epitope immunogenicity revealed through a consortium approach improve neoantigen prediction

Wells, D. K., van Buuren, M. M., Dang, K. K., Hubbard-Lucey, V. M., Sheehan, K. C. F., Campbell, K. M., Lamb, A., Ward, J. P., Sidney, J., Blazquez, A. B., et al. (2020) · Cell

vaccines and immunoinformatics approachesCancer Immunotherapy and Biomarkers

Cited by 538