Publications of Mark E. Sherman
2022
Papers in international journals
- C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. Horlings, W. Weichert, J. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J. Bokhorst, J. van der Laak and F. Ciompi, "Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer.", NPJ breast cancer, 2022;8(1):120.
- J. Ogony, T. de Bel, D. Radisky, J. Kachergus, E. Thompson, A. Degnim, K. Ruddy, T. Hilton, M. Stallings-Mann, C. Vachon, T. Hoskin, M. Heckman, R. Vierkant, L. White, R. Moore, J. Carter, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, S. Winham, J. van der Laak and M. Sherman, "Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence", Breast Cancer Research, 2022;24.
- M. Sherman, T. de Bel, M. Heckman, L. White, J. Ogony, M. Stallings-Mann, T. Hilton, A. Degnim, R. Vierkant, T. Hoskin, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, J. Carter, S. Winham, D. Radisky and J. van der Laak, "Serum hormone levels and normal breast histology among premenopausal women", Breast Cancer Research and Treatment, 2022;194:149-158.
- T. de Bel, G. Litjens, J. Ogony, M. Stallings-Mann, J. Carter, T. Hilton, D. Radisky, R. Vierkant, B. Broderick, T. Hoskin, S. Winham, M. Frost, D. Visscher, T. Allers, A. Degnim, M. Sherman and J. van der Laak, "Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning", npj Breast Cancer, 2022;8.