Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
Abstract: Power networks are vital to society, yet service outages and faults can have devastating consequences. This study introduces a novel integration of machine learning and data augmentation ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Valve announced a new Steam Machine this week, and while I think it’s going to have a major impact on the next generation of gaming hardware – however PC-like that looks – there’s still one big ...
Just how powerful will the Steam Machine be? Based on expert analysis of the specs revealed by Valve when it announced the Steam Machine on Wednesday, its new compact, console-like gaming PC is aimed ...
Steam Machines are back for the first time since Valve teamed up with manufacturers like Alienware and Lenovo back in the 2010s. But while those original console-PC hybrids failed because of a lack of ...
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In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
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