This article discusses the use of Deep Learning to predict MSI status from histopathology images in colorectal cancer patients. The model was trained on…
Browsing: Histopathology
DEPLOY is a deep learning framework that uses histopathology and DNA methylation to accurately predict and classify tumor types. It combines indirect and direct…
The use of transformers, a type of machine learning model, has shown promising results in both natural language processing and vision tasks. These models…
DeepDOF-SE is a deep-learning-enabled microscope that can rapidly scan intact tissue at cellular resolution without the need for physical sectioning. It uses inexpensive vital…
The article discusses the issue of color and texture variations in histopathology images due to differences in staining conditions and imaging devices between hospitals.…
A computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex has been developed using deep learning and…
This article discusses the use of deep learning techniques in the diagnosis and grading of gliomas, a type of primary brain tumor. The proposed…
Researchers from the RIKEN Center for Advanced Intelligence Project (AIP) in Japan have developed an artificial intelligence (AI) framework capable of extracting interpretable features…
Federated learning is a distributed learning framework that enables multi-institutional collaborations on decentralized data with improved protection for each collaborator’s data privacy. This paper…
This study proposed a robust and computationally efficient fully automated Renal Cell Carcinoma Grading Network (RCCGNet) from kidney histopathology images. The proposed RCCGNet contains…