As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the ...

Especially when it comes to manufacturing, problem-solving is an art. Every day, companies within this industry face challenges that test their processes, products and, ultimately, their bottom line.

Recently, model-based reinforcement learning has been considered a crucial approach to applying reinforcement learning in the physical world, primarily due to its efficient utilization of samples.

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Researchers at MIT have developed a ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...