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

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 ...

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

Background While maternal depression and anxiety have been linked to adverse childhood respiratory outcomes, the role of ...

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

Introduction Caesarean section rates have increased globally, exceeding the WHO’s recommended threshold of 15%. Understanding ...

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 ...

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

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

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

Metabolic syndrome affects nearly 40% of adults, with sharper increases seen in older age groups and non-Hispanic Black ...

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