wearable device

PCA-BM includes two models: “Automatic BMs Segmentation AI Model” and " Distant Brain Failure Prediction Model". The former one uses C2FNAS (coarse to fine network architecture search) to detect the location, size, and the number of brain metastases. The latter uses radiomics to extract numerous radiographic features and employs machine learning methods such as XGBoost to establish a prognostic model of brain metastases. PCA-BM provides more precision treatment decisions for patients and improves personalized and accurate overall stereotactic radiosurgery planning.