Abstract: This research aims to explore the use of modern complex defensive machine learning algorithms in the provision of predictive analytics for health improvement. Incorporating electronic health ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Optimize your Yahoo fantasy football draft with a highlighted cheat sheet featuring 2025 player projections, breakout candidates, sleepers, and positional analysis for every NFL team. The fantasy ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science ...

After a couple of volatile weeks, Bitcoin (BTC) experienced a modest rebound on Monday, July 28. However, with major U.S. crypto policy reports due July 30, the flagship digital asset could still ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Abstract: Healthcare has increasingly embraced machine learning (ML) algorithms, which have been shown to enhance diagnostic accuracy, treatment effectiveness, and ultimately improve patient outcomes.