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A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic.
(AMER SOC CLINICAL ONCOLOGY, 2019-04-17)
PURPOSE: Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the ...
The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.
(BMC, 2020-06-01)
BACKGROUND: Limited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification. METHODS: Three hundred twenty-nine ...
Identification of a prognostic signature in colorectal cancer using combinatorial algorithm-driven analysis.
(WILEY, 2022-05-01)
Colorectal carcinoma is one of the most common types of malignancy and a leading cause of cancer-related death. Although clinicopathological parameters provide invaluable prognostic information, the accuracy of prognosis ...
Exploring the immune microenvironment in small bowel adenocarcinoma using digital image analysis.
(PUBLIC LIBRARY SCIENCE, 2023-08-01)
BACKGROUND: Small bowel adenocarcinoma (SBA) is a rare malignancy of the small intestine associated with late stage diagnosis and poor survival outcome. High expression of immune cells and immune checkpoint biomarkers ...