Please provide your email address to receive an email when new articles are posted on . Explainable machine learning can offer accurate diagnoses and identify causes of chronic kidney disease in early ...

While the idea of a black box is intriguing, it can miss the point. Placing information into a black box that spits out a solution is valuable but understanding what’s going on in that black box is ...

Systematic mapping of gender disparities in oncology publications of north African countries: The GEORGiNA study. This is an ASCO Meeting Abstract from the ASCO Breakthrough: A Global Summit for ...

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 ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning ...

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