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

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, ...

This prediction approach achieves higher agreement in predictions by optimizing the concordance correlation coefficient (CCC), which measures how well pairs of observations fall on the 45-degree line ...

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 ...

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.

Injury Probability Models Explained. Learn how smart data and clear numbers improve sports prediction while protecting ...

Researchers reported on a prediction model developed to determine which patients with spinal metastases were likely to benefit from surgery.

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.