Projects Last Projects

Analysis & Prediction of Breast Cancer Survival Using Hematoxylin and Eosin (H&E) Images Based on Deep Learning Algorithms

Omer Taub and Nativ Levy

Supervised by Gill Shamai and Shachar Cohen

Abstract

Breast cancer remains a leading cause of mortality among women
globally despite advances in treatment. Accurate prediction of
patient survival outcomes remains a challenge and is crucial for guiding
treatment decisions.
This project aims to enhance prognosis by leveraging deep learning
techniques to analyze H&E stained images, with the goal of
developing a model that provides more reliable survival predictions
and ultimately improves patient outcomes.

Pictures

Project Analysis & Prediction of Breast Cancer Survival Using Hematoxylin and Eosin (H&E) Images Based on Deep Learning Algorithms Picture 1