To achieve true autonomy, AI systems must integrate both neural networks (for learning and pattern recognition) and symbolic AI (for structured knowledge and reasoning). This fusion, known as ...

Researchers have developed a graph-based expert system that improves the accuracy and prediction stability of automated bank ...

For rare diseases, AI-driven repurposing fills a critical gap. With more than 7000 rare diseases and only a small percentage ...

Foundational machine learning models are typically large — trained using unlabeled data at scale, to further be adapted to a wide spectrum of specific tasks. But, given their depth, these models also ...

Models built on machine learning in health care can be victims of their own success, according to researchers at the Icahn School of Medicine and the University of Michigan. Their study assessed the ...

Machine learning models can be incredibly valuable tools for business leaders. They can aid in interpreting historic data, making decisions for future initiatives, helping to improve the customer ...

Machine learning startup Predibase Inc. today announced the commercial availability of its low-code declarative machine learning platform for artificial intelligence developers, adding new features ...

Artificial intelligence models, pretrained on vast datasets, significantly outperformed a standard baseline model in identifying nonmelanoma skin cancers (NMSC) from digital images of tissue samples, ...

A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with ...