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 ...

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

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

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

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 ...

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 ...

Logistic regression, 2. Random forest, 3. Decision tree, and 4. eXtreme Gradient Boosting (XGBoost). All models were built using the the Python scikit-learn library.