TY  - GEN
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.
DO  - 10.6083/ks65hc876
DO  - DOI
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.
T1  - Artificially intelligent pathology
DA  - 2020
AU  - Schau, Geoffrey F.
L1  - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf
PB  - Oregon Health and Science University
PY  - 2020
ID  - 8668
L4  - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf
KW  - Artificial Intelligence
KW  - Data Management
KW  - Pathology
KW  - computer assisted image processing
TI  - Artificially intelligent pathology
Y1  - 2020
L2  - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf
LK  - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf
UR  - https://digitalcollections.ohsu.edu/record/8668/files/Schau.Geoffrey.2020.pdf
ER  -