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Image credit: DreamStudio What is the first thing you do when starting a new machine learning project?

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.

The majority of machine learning projects fail. How can you insure the success of your high impact project?

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.

It’s easy to measure greenhouse gases but hard to know where they come from.

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