For inpatients with cirrhosis, a machine learning (ML) model using random forest (RF) analysis is superior for prediction of ...

Every year, thousands of new materials are created, yet many never reach their full potential because their applications aren't immediately obvious—a challenge University of Toronto researchers aim to ...

Researchers employed a machine learning technique known as random forest analysis and found that it significantly outperformed traditional methods in predicting which hospitalized patients with ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Researchers employed a machine learning technique known as random forest analysis and found that it significantly ...

A printed circuit board (PCB) surface-mounted devices (SMDs) defect detection algorithm based on random forest (RF) was proposed to detect pin defects, resistor defects, and capacitor defects. It can ...

In this paper, we evaluate the effectiveness of the Random Forest algorithm in detecting intrusions within IoT environments through features selection analysis. We utilize the Network Intrusion ...

Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP) - instadeepai/mlip ...

AI offers promise in the realm of chronic disease management, including diabetes, obesity, and PCOS, but must be approached with caution.

Northwestern Engineering faculty and students participated in the annual forum for advances in theory, empirics, and ...