Using machine learning models researchers have found in a new study that increased physical activity and reduced sedentary ...

This study highlights the potential of heart rate variability as an early indicator of gestational diabetes, facilitating ...

The results showed that the random forest model performed the best, with an accuracy of 0.84 and an F1 value of 0.77. Compared with traditional diabetes detection methods, the accuracy of diabetes ...

The primary objective is to analyze existing supervised machine learning algorithms like ... technique is the most suitable for predicting diabetes as well as to evaluate by how much ensemble methods ...

15. Gao, J, and Liu, Y. Prediction, and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a ...

Results presented at the 85th Scientific Sessions of the American Diabetes Association in Chicago highlight the potential for ...

A new study offers insight into the health and lifestyle indicators—including diet, physical activity and weight—that align ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

Background Diagnosing the presence of metastasis of pancreatic cancer is pivotal for patient management and treatment, with ...