Phys.org

Algorithm extracts interpretable information from weather data to improve AI models

Long-term weather forecasting is a difficult task, partly because weather systems are inherently chaotic. Though mathematical equations can approximate the underlying physics of weather, tiny ...
Nature

Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence

The prediction of patient disease risk via computed tomography (CT) images and artificial intelligence techniques shows great potential. However, training a robust artificial intelligence model ...
Nature

An interpretable machine learning model using routine clinical data for early recurrence prediction in hepatocellular carcinoma

Accurate prediction of early postoperative recurrence in hepatocellular carcinoma (HCC) remains challenging. We developed and validated an interpretable machine learning model to predict early ...
ascopubs.org

Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...
MedPage Today

AI Model Stratifies Late Recurrence Risk in HR-Positive Breast Cancer

At the San Antonio Breast Cancer Symposium, researchers presented findings on Clarity BCR, a multimodal multitask deep-learning algorithm that aims to estimate late distant recurrence risk in hormone ...