Recent advancements in artificial intelligence have introduced powerful tools transforming medical diagnostics. Mount Sinai researchers developed a Graph Neural Network model to guide anticoagulation decisions in atrial fibrillation with unprecedented individualization. Elsewhere, new explainable AI frameworks enhance liver cirrhosis detection accuracy, and machine learning algorithms predict pituitary adenoma recurrence. Such innovations underscore AI’s growing utility in precision medicine, prognostics, and therapeutic optimization, promising improved patient outcomes across various diseases.