Smarter maps reveal four decades of change

Tracking land cover over long time periods is essential for understanding climate, ecosystems, and human development, yet many annual maps are inconsistent from year to year. This study presents a new ...

Improving Soil Moisture Retrieval by Combining MODIS BRDF and CYGNSS Data

A new soil-moisture retrieval strategy has improved the accuracy of satellite-based moisture mapping by combining microwave ...
KDFW

FIFA World Cup: Random Selection Draw for single-match tickets open for applications

The third phase of ticket sales for the FIFA World Cup 2026, the Random Selection Draw, is now open for applications. This is the first time fans can apply for single-match tickets based on the ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
ahajournals.org

Applying a Random Forest Approach in Predicting Health Status in Patients with Carotid Artery Stenosis 30 Days Post Stenting

Approximately 20% of ischemic strokes in the United States result from carotid artery stenosis. Carotid artery stenting (CAS) can reduce stroke risk, but variability in poststenting health outcomes ...
IEEE

Research on Network Intrusion Detection in Random Forest Based on Pearson Feature Selection

Abstract: With the continuous escalation of cyber-attacks, improving the accuracy of network intrusion detection systems has become crucial. In this study, a new Random Forest algorithm—the Random ...
Frontiers

A risk prediction model for neovascular glaucoma secondary to proliferative diabetic retinopathy based on Boruta feature selection and random forest

Neovascular glaucoma (NVG) is one of the most severe complications of proliferative diabetic retinopathy (PDR), carrying a high risk of blindness. Establishing an effective risk prediction model can ...