Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

Read more about AI can’t deliver climate gains without strong governance and capacity building on Devdiscourse ...

Scientists at the European Centre for Medium-Range Weather Forecasts have unveiled a machine learning technique that pinpoints optimal locations for tree planting, offering a powerful tool for climate ...

Zoonova AI today announced the launch of Alpha AI, a new investing platform designed to make advanced market intelligence more accessible through a natural-language AI Command Center. Alpha AI ...

As climate change intensifies and global food security faces pressures, accurate monitoring of crop phenology—especially ...

A skin cancer diagnosis can seem to arrive out of nowhere. But buried in years of health records, prescription histories, and ...

Solar flares strong enough to knock out satellites and buckle power grids are, by definition, rare. That rarity is exactly ...

The Office of Undergraduate Research organizes the Symposium of Student Scholars twice per year, offering students a unique ...

Newly published research suggests that AI can subliminally learn. This is exciting but also disconcerting. Evil AI could ...