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 ...

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 ...

Discover the ultimate roadmap to mastering machine learning skills in 2025. Learn Python, deep learning, and more to boost ...

Apart from simple diagnosis, the study takes an important step toward predictive health monitoring by modeling the risk of ...

Prediction of landslide susceptibility is of vital importance as a research topic in the field of disaster management. Landslides are considered as natural disasters that frequently occur in Sri Lanka ...

Machine learning algorithms are frequently applied in data mining applications. Many of the tasks in this domain concern high-dimensional data. Consequently, these tasks are often complex and ...