Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for clean-energy reactions are screened, identified, and validated across ...
BENGALURU Built by IIT alumni and engineers from Flipkart and Uber, padho.ai has launched an AI-powered learning platform that combines a Digital Brain Twin, an advanced interactive learning interface ...
Atmospheric aerosols influence climate forcing, air quality, visibility, and human health, but their properties vary widely across space and time. Satellite instruments equipped with multi-angle and ...
Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...
Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...
Background and objectives: The aim of this study is to evaluate the performance of DL algorithms in diagnosing early gastric cancer (EGC) using white light endoscopic images. Methods: A systematic ...
Abstract: Type 1 Diabetes (T1D) is a chronic metabolic disease characterized by elevated blood glucose (BG) concentrations, resulting from the immune-mediated destruction of insulin-producing ...
A total of 17.9 million people were estimated to be living with rheumatoid arthritis globally in 2021, representing a 13.2% increase in incidence since 1990. The global burden of rheumatoid arthritis ...
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Background and Aims: Obstructive coronary artery disease (CAD) can lead to myocardial infarction or cardiac death. The accuracy of conventional risk prediction models is limited, leading to excessive ...
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