Artificial intelligence and deep learning are increasingly applied to improve diagnostic accuracy and efficiency in medical imaging. Ultromics recently demonstrated enhanced echocardiogram analysis for early cardiac amyloidosis detection, while Stanford spinout Pumpkinseed develops silicon chip-based peptide sequencing technology with applications in immunology and oncology. Additionally, AI-driven models show promise in improving bronchoscopy accuracy for lung lesions. These advancements offer potential to transform clinical workflows, enable earlier disease detection, and personalize patient care through integrated computational and imaging approaches.