The researchers argue that their findings, published in Scientific Reports, could help clinicians anticipate which patients ...

The researchers also argue that explainable AI models are essential for ensuring fairness and accountability in policy design. In traditional statistical models, the relationships between variables ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Overview:  Python and Jupyter offer a simple, powerful setup for beginner-friendly data science learning. Real-world datasets ...

A Scientific Reports study developed a pattern neural network that integrates total antioxidant status with clinical and ...

Researchers explore the use of smartphones coupled with clinical scores to evaluate motor function and predict dopamine ...

Overview: Predictive models turn historical data into reliable forecasts that support accurate planning across ...

New NIH-funded research has led to an AI model that may better predict which children are at high risk for sepsis — before ...

Machine learning models delivered the strongest performance across nearly all evaluation metrics. CHAID and CART provided the highest and most stable sensitivity, accuracy and discriminatory power, ...

Researchers found that long-term driving behavior can reveal early signs of cognitive decline years before clinical diagnosis.

Objective To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.

What if AI could tell you when your diabetes might get worse—before it happens? From blood sugar trends to retinal scans, ...