In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...
Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...
Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.
(2026) AI Assisted Material Selection Framework for Corrosion Resistant Steels in Onshore Oil and Gas Pipelines. Open Journal ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Water leaves a memory in the land. Even after thousands of years, it lingers as faint ridges and subtle curves that only ...
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 ...
Background: Diabetic peripheral neuropathy (DPN) is a prevalent and highly disabling complication of diabetes mellitus, associated with markedly increased rates of disability and mortality. Timely ...
Abstract: This paper presents a novel approach to optimizing vehicle-to-grid (V2G) enhanced energy management in microgrid systems through machine learning-based forecasting. The proposed system ...
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