Tag: digital pathology

An in-house deep learning model detected all bladder cancer lymph node metastases on digitized slides while more than halving pathologist ...

Evaluating lung adenocarcinoma whole-slide images revealed that mild JPEG2000 compression reduces storage requirements by approximately 90% while maintaining deep learning ...

A large-scale retrospective analysis of 1,751 surgical meningioma cases reveals that digital quantification of phosphorylated retinoblastoma protein independently predicts tumor ...

Researchers have introduced HiViTAlign, a computational pipeline that pairs a vision transformer with graph clustering to reconstruct fragmented histological sections ...

Researchers from the European OPTIMA consortium have presented computational workflows integrating clinical records, genomic profiles, mammograms, and digital histopathology to ...

A narrative review indicates that telepathology adoption is expanding across India, though infrastructure costs and regulatory hurdles remain key barriers.

A review in Cell Division evaluates AI and machine learning models for pancreatic cancer diagnosis, highlighting their high reliability in ...

A new review finds AI-derived biomarkers show promising, though variable, performance in predicting cancer immunotherapy response across tumor types.

A retrospective study in Diagnostic Pathology found that a biopsy-trained AI algorithm achieved 94.3% sensitivity for detecting incidental prostate adenocarcinoma ...

Veterinary researchers evaluated automated nuclei quantification across experimental and forensic porcine skin wounds, finding age-related density declines that vary significantly ...