Histopathology

Building Robust AI Solutions for Whole Slide Images

Building Robust AI Solutions for Whole Slide Images

A great deal of focus in the pathology AI world is placed on creating models.

Continue Reading
Predicting Molecular Tumor Biomarkers from H&E: A Review of the State-of-the-Art

Predicting Molecular Tumor Biomarkers from H&E: A Review of the State-of-the-Art

New deep learning technology using H&E images has created an alternative path for molecular diagnostics Breast cancer is a clear example of the effectiveness of precision medicine.

Continue Reading
5 Ways to Make Histopathology Image Models More Robust to Domain Shifts

5 Ways to Make Histopathology Image Models More Robust to Domain Shifts

Exploring a variety of approaches: stain normalization, color augmentation, adversarial domain adaptation, model adaptation, and finetuning One of the largest challenges in histopathology image analysis is creating models that are robust to the variations across different labs and imaging systems.

Continue Reading
Finding prognostic patterns in gigapixel images

Finding prognostic patterns in gigapixel images

Advances in AI applying deep learning to digital pathology images can stratify patients by risk.

Continue Reading
Survival Models for Histopathology

Survival Models for Histopathology

A review of machine learning techniques for predicting patient outcomes from whole slide images.

Continue Reading
From Patches to Slides: How to Train Deep Learning Models on Gigapixel Images With Weak Supervision

From Patches to Slides: How to Train Deep Learning Models on Gigapixel Images With Weak Supervision

A review of techniques for modeling whole slide histology images and recommendations for different situations.

Continue Reading