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 ...

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 ...

Explainability tools are commonly used in AI development to provide visibility into how models interpret data. In healthcare machine learning systems, explainability techniques may highlight factors ...

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 ...

Responsible AI involves designing machine learning systems that are transparent, fair, and accountable. In the context of healthcare, responsible AI also includes protecting patient privacy, ensuring ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

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

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...