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

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

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

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 ...

It also evaluates AI’s role in automation and prediction through portfolio management, predictive analysis, and risk mitigation, emphasizing advanced machine learning techniques, including deep ...

Researchers developed a machine learning technique to predict obesity risk by analyzing sociodemographic, lifestyle, and health factors. The study, which achieved 79% accuracy, identified significant ...

To generate large and highly detailed forest maps, the researchers trained a type of machine learning algorithm called a deep neural network using images of the tree canopy and other sensor data ...

To generate large and highly detailed forest maps, the researchers trained a type of machine learning algorithm called a deep neural network using images of the tree canopy and other sensor data ...