Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

The global shift toward digital banking has been dramatic, with the volume of cashless transactions increasing year over year. While this growth signals progress in financial technology, it has also ...

Background There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior ...

In an age where data drives decisions and automation defines excellence, the insurance industry stands at the cusp of a digital renaissance. At the ...

Recent scientific article explores the use of machine learning techniques to identify the key risk factors associated with ...

This study published in Robot Learning has been focused on water analysis using the combination of decision making and machine learning for a recently developed robotic system. The unique procedure ...

Random Forest and Extreme Gradient Boosting (XGBoost) were found to provide the highest performance for injury risk prediction. Logistic regression outperformed ML methods in 4 out of 12 studies.