Automatic Diagnosis

Automatic diagnosis leverages artificial intelligence to analyze various medical data (e.g., images, signals, patient histories) for faster and more accurate disease detection. Current research emphasizes improving model accuracy and interpretability using techniques like convolutional neural networks (CNNs), transformers, and ensemble methods, often incorporating explainable AI (XAI) to enhance trust and clinical adoption. This field holds significant promise for improving healthcare efficiency, enabling earlier disease detection, and potentially reducing diagnostic errors, particularly in resource-constrained settings.