Disease Prediction

Disease prediction research aims to develop accurate and timely models for identifying individuals at risk of various illnesses, improving early intervention and preventative care. Current efforts focus on leveraging diverse data sources (e.g., electronic health records, medical images, patient narratives) and advanced machine learning techniques, including large language models, transformers, convolutional neural networks, and graph neural networks, often incorporating feature selection and data augmentation strategies to enhance performance. These advancements hold significant potential for improving healthcare outcomes through personalized risk assessment, optimized resource allocation, and more effective disease management strategies.