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 ...

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

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 ...

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

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

Background Adverse childhood experiences (ACEs) are traumatic events that occur before a child reaches the age of 15 with ...

Longer PTR times during thrombectomy significantly increase the likelihood of death or hospice discharge and raise acute stroke care costs.

A tool that incorporates five predictors helps accurately identify patients with dermatomyositis who have an increased likelihood of concomitant cancer and can be used to help with early detection.

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 ...

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

The likelihood for self-reported prediabetes was significantly elevated among adults who smoked combustible cigarettes only, ...