In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...
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Making simulations more accurate than ever with deep learning
Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...
Logistic regression is the most cost-effective model for medial vascular calcification classification, with a mean ICER of $278 using five low-cost features. Despite similar diagnostic accuracy, ...
Strokes are a leading cause of death and disability worldwide, and prompt diagnosis and treatment are crucial to preventing devastating outcomes. However, diagnosing strokes can be challenging due to ...
Georgia Southern University researchers develop a machine learning model with 97.97% accuracy in earthquake forecasting. STATESBORO, GA, UNITED STATES, October 29 ...
In a significant advance for improving weather forecast accuracy, Google DeepMind scientists have developed a weather model that largely beats the world's most accurate modeling system. Why it matters ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
Identifying optimal catalyst materials for specific reactions is crucial to advance energy storage technologies and sustainable chemical processes. To screen catalysts, scientists must understand ...
The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...
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