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 ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using comprehensive health examination data from nearly 37 701 individuals.Methods ...

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.

Introduction Prescribing high-dose antipsychotics is typically reserved for individuals with treatment-resistant severe ...

A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Self-organizing maps, and the machine learning protocol involved in creating them, have been in use since the 1980s, Lawrence ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.