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 ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...

In an era where artificial intelligence drives critical business decisions, Nikhil Dodda emphasizes that maintaining machine learning model performance is as crucial as building them. Model deployment ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

It's notoriously difficult to consistently measure the energy usage of AI models, but DARPA wants to put an end to that uncertainty with new "energy-aware" machine learning systems. … The Mapping ...

Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

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