Medical AI Algorithm

Medical AI algorithms aim to improve healthcare diagnostics and treatment through machine learning, focusing on achieving performance comparable to or exceeding human clinicians. Current research emphasizes addressing challenges like data scarcity (using synthetic data generation via GANs and diffusion models) and ensuring robust generalization across diverse datasets and clinical settings, including investigating the role of sample size in offsetting classification errors. These efforts are crucial for building trustworthy and equitable AI systems, requiring careful consideration of explainability (XAI) to understand model behavior and performance disparities across different sites and patient populations.