Pulmonology Advisor

New Model Could Predict Risk of Critical Illness in CTD-ILD

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

Hybrid machine learning framework for predictive maintenance and anomaly detection in lithium-ion batteries using enhanced random forest

The critical necessity for sophisticated predictive maintenance solutions to optimize performance and extend lifespan is underscored by the widespread adoption of lithium-ion batteries across ...
Nature

Machine learning-based risk prediction model construction of difficult weaning in ICU patients with mechanical ventilation

In intensive care unit (ICU) patients undergoing mechanical ventilation (MV), the occurrence of difficult weaning contributes to increased ventilator-related complications, prolonged hospitalization ...
Visual Studio Magazine

Random Forest Regression Using C#

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 ...
Visual Studio Magazine

Random Forest Regression and Bagging Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...