Overview Machine learning offers efficiency at scale, but trust depends on understanding how decisions are madeAs machine ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

CERES program updates include operational satellite instruments, algorithm advancements, machine learning applications, and ongoing missions measuring Earth’s energy budget and climate system changes.

Researchers Yue Zhao and Kang Pu from Stony Brook University—in collaboration with Ecosuite's John Gorman and Philip Court, and leveraging historical datasets provided by Ecogy Energy—have devised a ...

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...