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

Customer churn remains a huge issue for telcos, but AI could be the key to changing that. Or, it could fail to live up to its ...

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 ...

MFIs rely on standardized interest rate systems that treat borrowers uniformly, regardless of the individual likelihood of ...

By Priyanjana Pramanik, MSc. By combining oxidative stress biology with advanced machine learning, researchers show how a ...

By Dr. Liji Thomas, MD By pairing everyday smartphone motion data with established clinical scores, researchers demonstrate a ...

A highly accurate AI model improves prediabetes prediction by integrating antioxidant status with standard risk factors.

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 ...

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

The test, developed by Astrin Biosciences, utilizes deep proteomic profiling and a machine learning classifier to identify ...

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