Personalized Cancer

Personalized cancer medicine aims to tailor cancer treatments to individual patients based on their unique tumor characteristics and genetic makeup. Current research heavily utilizes artificial intelligence, particularly deep learning models like transformers and graph neural networks, to analyze multi-modal data (e.g., MRI, genomic data) for improved diagnosis, treatment prediction (e.g., response to chemotherapy or immunotherapy), and monitoring of tumor dynamics. This approach holds significant promise for improving treatment efficacy, reducing side effects, and ultimately enhancing patient outcomes by moving beyond one-size-fits-all approaches.