Introduction Beryllium exposure affects over one million individuals in the USA and remains an important cause of occupational lung disease. Up to 20% of exposed individuals develop beryllium ...

Predictive analytics allows data professionals to identify trends, forecast outcomes and test assumptions using data. When these capabilities are applied to simulation modeling, they make models more ...

Predictive modeling in archaeological site location combines statistical and computational techniques with spatial analysis to estimate the likelihood of undiscovered cultural heritage across diverse ...

A simulation study shows a safety-constrained nonlinear model predictive controller can keep a virtual autonomous vehicle ...

One of the simplest, most straightforward forms of AI is the predictive model. The predictive model, which uses the same kind of logic that powers large language models, such as GPT-4, might already ...

Thought LeaderDr. James McDonaghPrincipal Applied AI ScientistApconiX You have worked across the full drug development pipeline. How has that experience shaped your view of where AI can have the ...

The semiconductor industry, as always, is at the forefront of transformational technological innovation, driving escalating complexity of manufacturing processes that extend time-to-market delivery, ...

A retrospective study of 449 patients found that a LightGBM machine learning model predicted carotid plaque instability with ...

Attribution isn't going obsolete overnight, but its role is changing, and marketers should treat this as an infrastructure ...

Models built on machine learning in health care can be victims of their own success, according to researchers at the Icahn School of Medicine and the University of Michigan. Their study assessed the ...

A new breed of models has rejuvenated predictive AI. But successful deployment demands a new business-value playbook.