Prediction of RAS mutation in cancer tissue

Deep learning methods for prediction of RAS mutation status in colorectal cancer tissue

Research Goal :

Training and validating different models on 27,000+ images of H&E stained tissue.

Kelvin Usage :

Due to the group using kelvin2 for this experimental project, many techniques were explored, each technique requiring a huge amount of proccessing power.

This Kelvin2 environment allowed the group to submit scripts to be ran on state-of-the-art machine learning optimised GPUs, which meant they could complete in a matter of hours, rather than a matter of days. They would also submit multiple scripts at the same time, which significantly sped up comparisons.

The group states " The Kelvin2 computing environment was instrumental to the success of our project ".

 

RAS Protein Structure