Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree ...
Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...
Deep learning detects foodborne bacteria within three hours by eliminating debris misclassifications
Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in ...
Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...
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How are QA teams using machine learning to predict test failures in real time?
QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
A UT chemist says it is now time to develop tests for microplastics, similar to tests for other toxic threats.
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