AI model development is evolving fast. Discover which countries are leading in 2025, how many notable AI models exist, and ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

More Americans are wondering if digital surveillance has gone too far, with growing concerns about privacy. They question, ...

Objectives The association between smoking and patients with schizophrenia has been established through epidemiological ...

A I vision models have improved dramatically over the past decade. Yet these gains have led to neural networks which, though effective, don’t share many characteristics with human vision. For example, ...

Develop an in-depth understanding of machine learning models and learn to apply them to real-world problems. Accelerate your career in engineering or data science on this online and part-time Master's ...

The research aims to optimize agriculture using data science techniques. Agriculture is a critical sector for sustaining life on earth, and optimizing it can enhance food security and increase the ...

UCLA researchers have developed an AI system that turns fragmented electronic health records (EHR) normally in tables into readable narratives, allowing artificial intelligence to make sense of ...

By leveraging neural networks, the emerging field of scientific machine learning (SciML) offers novel approaches to address complex problems governed by partial differential equations (PDEs). In ...

This study presents an innovative supervised machine learning (ML) model to predict the reaction yield of the vanadium-catalyzed epoxidation of small alcohols and alkenes. Our framework uncovers ...

It is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. This hard cover book has 738 pages in full colour, ...