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

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 ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Enterprise software is undergoing a major transformation as machine learning becomes deeply embedded into core digital products. Organizations are no longer using ML only for experimental analytics; ...

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 ...

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, ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

AI systems already decide how ambulances are routed, how supply chains operate and how autonomous drones plan their missions. Yet when those systems make a risky or counterintuitive choice, humans are ...