Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Scientists have created an AI model that forecasts moderate heat stress—a major precursor to coral bleaching—at sites along ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

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Influence of Elephant-Driven Vegetation Structure and Altitudinal Gradient on the Occurrence of the Endemic Mount Cameroon Francolin ...

Forests are central to climate mitigation, yet tracking how fast they grow over decades remains difficult. A new satellite-based approach ...

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by laser-scanning technologies. Doing the same with forest data has proven far more ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

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

Abstract: Accurate carbon emission prediction is crucial for addressing climate change and promoting sustainable development. Traditional methods, primarily based on statistical regression models, ...

Abstract: A high-precision storm-time ionospheric model is crucial for both ionospheric research and precise positioning applications of global navigation satellite systems (GNSSs). However, the ...