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 ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Researchers at Beijing Normal University used advanced machine learning and satellite imagery to map forest management ...
In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: This paper aims to investigate the efficacy of EEG-based stress detection using a Random Forest classifier during the Stroop Test, a key psychological assessment probing cognitive functions ...
With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...
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: After all advancements in technology and times, prediction and prevention of heart diseases is still a major issue in modern days. Heart diseases play a major role in high death rate in ...
The compressive strength (CS) is the most important parameter in the design codes of reinforced concrete structures. The development of simple mathematical equations for the prediction of CS of ...
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