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 ...

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 ...

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 ...

There are three technical enablers “that repeatedly separate successful [AI] deployments from stalled pilots: trustworthy data pipelines, fit-for-purpose model selection, and lifestyle governance,” ...

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, ...

Northwestern Engineering researchers are making significant contributions to AI and robotics research by sharing new work at ...

AI medical diagnosis apps offer major opportunities in enhancing diagnostic accuracy and efficiency through AI algorithms.

Enterprise software is undergoing a major transformation as machine learning becomes deeply embedded into core digital ...