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) ...

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

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

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 ...

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

On the other hand, random forest and bagging tree regression models seem to have a good reputation among machine learning practitioners (most of my colleagues at least) because the models often work ...

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

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 ...