Berry, Gerald J.

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

Yu, K.-H., Zhang, C., Berry, G. J., Altman, R. B., Ré, C., Rubin, D. L., & Snyder, M. (2016) · Nature Communications

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 972

Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study

Yamashita, R., Long, J., Longacre, T., Peng, L., Berry, G., Martin, B., Higgins, J., Rubin, D. L., & Shen, J. (2021) · The Lancet Oncology

AI in cancer detectionGenetic factors in colorectal cancer

Cited by 391

Impact of a deep learning assistant on the histopathologic classification of liver cancer

Kiani, A., Uyumazturk, B., Rajpurkar, P., Wang, A., Gao, R., Jones, E., Yu, Y., Langlotz, C. P., Ball, R. L., Montine, T. J., et al. (2020) · npj Digital Medicine

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 325

Predictive radiogenomics modeling of EGFR mutation status in lung cancer

Gevaert, O., Echegaray, S., Khuong, A., Hoang, C. D., Shrager, J. B., Jensen, K. C., Berry, G. J., Guo, H. H., Lau, C., Plevritis, S. K., et al. (2017) · Scientific Reports

Radiomics and Machine Learning in Medical ImagingLung Cancer Diagnosis and Treatment

Cited by 160

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery

Chiou, S.-H., Tseng, D., Reuben, A., Mallajosyula, V., Molina, I. S., Conley, S., Wilhelmy, J., McSween, A. M., Yang, X., Nishimiya, D., et al. (2021) · Immunity

Cancer Immunotherapy and BiomarkersT-cell and B-cell Immunology

Cited by 133