A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

A machine learning-driven framework accurately predicts MPA exposure and supports individualized dosing in childhood-onset LN.

How will the public retain confidence in a system that rests on the painstaking articulation of reasoned logic as more and ...

Farming is changing from manual, experience-led observation to data-driven decision-making powered by advanced sensing systems and artificial intelligence. A new research paper titled “Fast Forward ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A growing body of peer-reviewed research is giving scientists new tools to isolate the distinct climate signals left behind by volcanic mega-eruptions and extreme wildfires, two forces that can alter ...

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...

Reported accuracies were 86% (Random Forest) and 96% (convolutional neural networks), positioning retinal imaging as a candidate scalable tool for underserved populations. AI-powered polarized-light ...

If a tree falls in the forest, it can create an opening for more incoming light, and that makes a significant impact on the surrounding environment, according to new research. An international science ...