Clinical Prediction

Clinical prediction research aims to develop accurate and reliable models for forecasting health outcomes, such as disease risk or patient survival, using diverse data sources like electronic health records and social media. Current efforts focus on integrating various machine learning techniques, including deep learning models and large language models (LLMs), often combined with traditional statistical methods to improve prediction accuracy and interpretability. This field is crucial for improving healthcare decision-making, enabling earlier interventions, and personalizing treatment plans, ultimately leading to better patient outcomes and more efficient healthcare resource allocation.