Artificial intelligence continues to make strides in healthcare, exemplified by a Graph Neural Network-based model developed at Mount Sinai for personalized anticoagulation decisions in atrial fibrillation patients, promising to optimize stroke prevention. In medical imaging, deep learning frameworks are outperforming traditional methods for lung nodule and mammogram classification, facilitating enhanced diagnostics. These advancements suggest a paradigm shift towards precision medicine, with AI improving both therapeutic decision-making and diagnostic accuracy across medical domains.