Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...

Artificial intelligence (AI) is set to transform the care of women with cancer. From early detection via digital phenotyping ...

The CT-based whole-lung radiomic nomogram accurately identifies AECOPD and offers a robust tool for clinical diagnosis and treatment planning.

A machine-learning breakthrough could lift the veil on Earth’s early history—and supercharge the search for alien life ...

Over the last decade, technology-assisted review (TAR) has become a preferred choice in the e-discovery toolkit. Now, as ...

While self-healing agentic test suites can help eliminate the manual intervention consuming engineering cycles, there are key strategies to make this approach successful.

Today, MLCommons announced new results for the MLPerf Training v5.1 benchmark suite, highlighting the rapid evolution and ...

The hybrid model is emerging as the framework for trustworthy AI in test analytics. It retains traceability and supports ...

The Tomorrow’s Quants series explores the skills needed by new quant recruits, drawing on a survey of 39 employers, and six ...

Banks aren't currently taking full advantage of AI, but a focused, future-ready banking AI strategy can deliver real impact.

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.