Researchers developed a new model to predict the likelihood of critical illness in patients with connective-tissue disease-associated ILD.

The machine learning algorithm and subsequent simulations are fueled by data, expert knowledge and statistical models ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

Our planet’s forests are undergoing a transformation that researchers are only now beginning to fully understand. Between 2001 and 2020, scientists tracked dramatic shifts in how forests are managed ...

Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...

Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

ABSTRACT: Accurate canopy height estimation is critical for forest management and carbon monitoring in Zambia’s ecologically diverse landscapes. This study developed a high-resolution canopy height ...

Forests occupy one third of the total land area of the Earth and hold around 80 per cent of the world’s terrestrial biodiversity. It is estimated that nearly one third of the global population depends ...