Innovations in artificial intelligence are transforming medical diagnostics with breakthroughs in tumor segmentation and imaging genomics. Researchers in Tokyo developed MHP-Net, an AI model that improves liver tumor detection on CT scans even with limited training data, as detailed in IEEE Access. Concurrently, imaging genomics integrates multi-modal data to link genetic features with clinical imaging phenotypes, empowering precision medicine across complex diseases. These technologies are poised to elevate diagnostic accuracy and therapeutic targeting in oncology and beyond.