Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative
information from digital histopathology images. AI is expected to reduce workload for human …

Precision oncology relies on the identification of targetable molecular alterations in tumor
tissues. In many tumor types, a limited set of molecular tests is currently part of standard …

Artificial intelligence (AI) can extract visual information from histopathological slides and
yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of …

Ovarian carcinoma has the highest mortality of all female reproductive cancers and current
treatment has become histotype-specific. Pathologists diagnose five common histotypes by …

Determining early-stage prognostic markers and stratifying patients for effective treatment
are two key challenges for improving outcomes for melanoma patients. Previous studies …

Whole slide images (WSI) are microscopy images of stained tissue slides routinely prepared
for diagnosis and treatment selection in medical practice. WSI are very large (gigapixel size) …

Over the last decade, supervised deep learning on manually annotated big data has been
progressing significantly on computer vision tasks. But, the application of deep learning in …

Analyzing high resolution whole slide images (WSIs) with regard to information across
multiple scales poses a significant challenge in digital pathology. Multi-instance learning …

Molecular and genomic properties are critical in selecting cancer treatments to target
individual tumors, particularly for immunotherapy. However, the methods to assess such …

Homologous recombination DNA-repair deficiency (HRD) is becoming a well-recognized
marker of platinum salt and polyADP-ribose polymerase inhibitor chemotherapies in ovarian …