Prognostic Prediction

Prognostic prediction aims to forecast the future state of a system or patient, enabling timely interventions and improved outcomes. Current research emphasizes the development of robust and interpretable models, employing diverse architectures such as graph neural networks, transformers, and convolutional neural networks, often incorporating multimodal data (e.g., images, text, sensor readings) and addressing challenges like data imbalance and missing values. This field holds significant importance across various domains, from predicting equipment failure in industrial settings to improving patient care through personalized risk stratification in healthcare.