Bias in AI isn’t just baked into the training data; it’s shaped by us and embedded in the broader ecosystem of human-AI ...

A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence's toughest challenges by ...

Institutional memory loss explains why so many AI debates feel stuck on repeat. The same hopes, fears, and technical arguments resurface because the field has not fully absorbed its own history. Until ...

Researchers demonstrate that misleading text in the real-world environment can hijack the decision-making of embodied AI systems without hacking their software. Self-driving cars, autonomous robots ...

Background Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by impairments in social ...

Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but ...

Handling missing data in administrative records using statistical and machine learning–based imputation techniques. The project compares Mean, Median, KNN, and MICE across different missingness levels ...

Background Up to half of patients with infective endocarditis (IE) require cardiac surgery. Although anaemia is common, its ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Objective: To construct a prediction model for teicoplanin (TEIC) plasma concentrations through machine learning and deep learning techniques in patients with liver disease using real-world clinical ...

Edward Khomotso Nkadimeng receives funding from the National Research Foundation. In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, an age ...