Biomarker Prediction

Biomarker prediction aims to identify and quantify disease indicators directly from medical images, such as histopathology slides or MRI scans, using machine learning. Current research heavily utilizes deep learning models, including vision transformers and convolutional neural networks, often employing multi-task learning and self-supervised pre-training strategies to improve accuracy and generalizability across diverse cancer types and biomarkers. This field holds significant promise for accelerating diagnosis, personalizing treatment selection, and improving patient outcomes by providing a faster, cheaper, and potentially more comprehensive alternative to traditional molecular assays.