Prognosis Model

Prognosis models aim to predict the likely course of a disease or condition, assisting in personalized treatment and improved patient outcomes. Current research emphasizes developing more accurate and interpretable models, often employing deep learning architectures like convolutional neural networks and transformers, sometimes incorporating human-in-the-loop approaches to refine predictions and address data limitations. These advancements are improving the prediction of various diseases, from melanoma to Huntington's disease and colorectal liver metastases, leveraging diverse data sources including medical images, biomedical signals, and clinical records, and showing promise for enhancing clinical decision-making and precision medicine.