Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.
As microservices multiply, organizations need systems capable of interpreting and understanding impact, not just executing ...
Nandita Giri is a senior software engineer with experience at Amazon, Meta, and Microsoft. She recommends job seekers spend ...
Scholars and artists at Sorbonne University trained artificial intelligence to imitate the French playwright’s themes, ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
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 ...
Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how ...
The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning ...
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Study shows reliable model to predict licensure exam outcome
A study conducted by experts from the University of the Philippines-Diliman showed that logistic regression is a reliable model for predicting the performance of licensure examination takers. Released ...
Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...
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