A machine learning model for cancer staging, case study: uveal cancer

The fields of medicine and computer science have advanced in parallel, providing revolutionary techniques for the diagnosis and treatment of serious diseases. However, despite the accuracy of medical imaging devices, cancer remains a difficult diagnosis. To address this issue, artificial intelligence is increasingly being used for cancer detection. Our work involves in-depth research on the most effective machine learning methods to apply them in the field of medicine. Our key findings include high accuracy in staging uveal cancers using targeted techniques as GAN, and the development of a web application to assist physicians with prediction tasks.