Histopathology

Common challenges in machine learning for pathology.

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

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.

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.

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

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

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

Breast cancer is a clear example of the effectiveness of precision medicine.

New AI technology using H&E images creates an alternative path for molecular diagnostics Molecular properties are critical in selecting cancer treatments to target weaknesses of individual tumors.

Not all cancers are the same, so how can we identify the differences that we can’t see?

Artificial intelligence finds new insights into molecular tumor properties using a different view – images of cells and tissue.