Tadeo Ramirez-Parada studied the timing of plant flowering for his PhD — but he didn’t touch a single petal. Instead, he ...

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

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

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 ...

If you want to spoil a sailor's day, then a ship collision is the way to do it. That's why Texas A&M University has come up ...

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

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

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of these environments lack natural or artificial light, making it difficult for ...

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

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...