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) ...

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

Ophthalmology Times connects eye care professionals with surgery, imaging, gene therapy, & diagnostic advances to enhance clinical and patient care.

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

Random forest regression is an integrated learning method that combines multiple decision tree models into a more powerful model that can effectively avoid overfitting problems and can handle ...

ML models were developed using random forest survival methods. The ground truth outcome was abnormal lymphocytosis associated with CLL and monoclonal B-cell lymphocytosis diagnosis: ALC ≥5 × 10 9 /L ...

Recent study focused on predicting short birth intervals (defined as less than 33 months) among reproductive-age women in ...

The life and health insurance industry landscape across the globe is now confronting mounting challenges such as increasingly ...

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 ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...