In the field of medical image analysis, the integration of machine learning (ML) models has significantly enhanced the process of identifying and diagnosing Alzheimer’s disease. However, the opacity ...

The SAFEXPLAIN project, formed by an inter-disciplinary consortium of six partners coordinated by the Barcelona ...

Testing and validating AI data sets helps ensure they are diverse and representative. “Developers use the Responsible AI Toolkit to assess bias in data sets and ensure transparency through ...

Translator’s implementation of Statistical Machine Translation (SMT) is built on more than a decade of natural-language research at Microsoft. Rather than writing hand-crafted rules to translate ...

Designing, building, and applying new technologies—especially those that include artificial intelligence—can be a double-edged sword: powerful and enabling on the one hand, but potentially biased and ...

Disease samples are naturally fewer than healthy samples which introduces bias in the training of machine learning (ML) models. Current study focuses in learning discriminating patterns between ...

More information: Zhenghao Yin et al, Experimental quantum-enhanced kernel-based machine learning on a photonic processor, Nature Photonics (2025). DOI: 10.1038/s41566-025-01682-5 ...