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 ...

Current global climate models (GCMs) support with high confidence the view that rising greenhouse gases and other anthropogenic forcings account for nearly all observed global surface warming—slightly ...

One would imagine that an AI capable of solving the hardest Olympiad problems would naturally produce novel scientific ...

AI systems are beginning to produce proof ideas that experts take seriously, even when final acceptance is still pending.

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the ...

Medical artificial intelligence is a hugely appealing concept. In theory, models can analyze vast amounts of information, recognize subtle patterns in data, and are never too tired or busy to provide ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...

Objectives: To develop and validate machine learning models to predict levodopa responsiveness of tremor in Parkinson’s disease (PD) patients. Methods: A total of 197 PD tremor patients underwent ...

Marketing mix models often fail because insights stop at analysis. Here's what it takes to turn MMM into a decision-driving capability. Marketing mix models aim to answer the marketer’s billion-dollar ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...