The ADB–Cornell study finds that machine learning poverty maps often misfire, overestimating welfare in poor, rural, ...

The results show that high ESG scores do not consistently enhance predictability. Across widely used error metrics, such as ...

Random Forest and Extreme Gradient Boosting (XGBoost) were found to provide the highest performance for injury risk prediction. Logistic regression outperformed ML methods in 4 out of 12 studies.

Ophthalmology Times connects eye care professionals with surgery, imaging, gene therapy, & diagnostic advances to enhance clinical and patient care.

Scientists use machine learning to predict diversity of tree species in forests Date: July 16, 2024 Source: PLOS Summary: Researchers used machine learning to generate highly detailed maps of over ...

To generate large and highly detailed forest maps, the researchers trained a type of machine learning algorithm called a deep neural network using images of the tree canopy and other sensor data ...