Medical Diagnosis

Medical diagnosis is undergoing a transformation driven by artificial intelligence, aiming to improve accuracy, efficiency, and accessibility of healthcare. Current research heavily utilizes machine learning models, including gradient boosting decision trees, support vector machines, convolutional neural networks, and transformers, often incorporating multimodal data (e.g., images, text, physiological signals) for enhanced diagnostic capabilities. This work addresses challenges such as algorithmic bias, interpretability, and the need for efficient and robust models, particularly in resource-constrained settings. The ultimate goal is to develop reliable and explainable AI-assisted diagnostic tools that augment clinical expertise and improve patient outcomes.