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

While self-healing agentic test suites can help eliminate the manual intervention consuming engineering cycles, there are key ...

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

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

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

AI’s future will be defined not by parameter counts, but by the integrity of the data that sustains it. Failures in ...

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

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

Community driven content discussing all aspects of software development from DevOps to design patterns. If you want to get certified as a Generative AI Leader by Google, you need to do more than just ...

The transformative powers of AI in manufacturing have not gone unnoticed—by hackers! The increased efficiency and ...