TY - GEN AB - Controlling cancer requires comprehensive understanding of the molecular, cellular, and organizational properties of tumor tissue. While clinical pathology has served as a gold standard for cancer diagnosis for over a century, the field continues to largely rely on visual inspection of sectioned and stained tissue under the microscope by expert pathologists. This work integrates deep learning systems for histopathological image analysis to quantitatively and qualitatively evaluate spatial characteristics of tumor biology to better guide clinical diagnosis and treatment of cancer. AU - Schau, Geoffrey F. DA - 2020 DO - 10.6083/ks65hc876 DO - DOI ID - 8668 KW - Artificial Intelligence KW - Data Management KW - Pathology KW - computer assisted image processing L1 - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf L2 - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf L4 - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf LK - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf N2 - Controlling cancer requires comprehensive understanding of the molecular, cellular, and organizational properties of tumor tissue. While clinical pathology has served as a gold standard for cancer diagnosis for over a century, the field continues to largely rely on visual inspection of sectioned and stained tissue under the microscope by expert pathologists. This work integrates deep learning systems for histopathological image analysis to quantitatively and qualitatively evaluate spatial characteristics of tumor biology to better guide clinical diagnosis and treatment of cancer. PB - Oregon Health and Science University PY - 2020 T1 - Artificially intelligent pathology TI - Artificially intelligent pathology UR - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf Y1 - 2020 ER -