Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...

Medulloblastoma the most common malignant pediatric brain tumor with a high risk of metastasis and poor survival outcomes. To delineate the metastatic microenvironment,, researchers in China have ...

In its primary application, mitosis detection in digital pathology, the system achieves strong predictive performance while maintaining 96% fidelity between predictions and explanations. Each decision ...

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...

The Next Frontier of Machine Learning: 2026 Breakthroughs and the Rise of World Models The landscape of artificial intelligence and ...

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...

Although the original Phase 3 A4 trial showed no statistically significant overall benefit for solanezumab (a humanized monoclonal antibody designed to treat Alzheimer’s disease by binding to and ...

With that in mind, “Regulatory agencies have to do more to provide practical guidance to the industry.” There are three technical enablers “that repeatedly separate successful [AI] deployments from ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as ...