Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Researchers developed a new model to predict the likelihood of critical illness in patients with connective-tissue disease-associated ILD.

Statisticians from across Europe teamed up to train a competition-predicting, machine learning algorithm ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

ABSTRACT: Biogas is gaining prominence as a renewable energy source with significant potential to reduce greenhouse gas emissions and mitigate environmental impacts associated with fossil fuels. This ...

MCED tests utilize liquid biopsies to detect multiple cancer types early, using ctDNA and other biomarkers analyzed by machine learning. Machine learning models, including deep learning, enhance MCED ...

Primary forests, or old-growth forests as they are sometimes called, are epicenters of rich biodiversity, are more resilient than younger forests, and store significantly more carbon than their ...

ABSTRACT: The paper reviews some of the major issues that occur in the application of big data analytics and predictive modeling in health, as obtained from the original study. It highlights ...