LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

An AI model with the potential to transform cervical spondylosis diagnosis by spotting subtle vertebral changes quickly and accurately.

The human brain is one of the most complex structures in nature, but the brain's origins stretch back hundreds of millions of years. A new study using AI deep-learning models has revealed more about ...

University of Warwick research warns that popular deep learning systems trained for cancer pathology may be relying on hidden ...

The earliest stage of drug discovery is governed by a simple constraint: there are far more possible drug-like molecules than any pharmaceutical laboratory could ever test. A new deep learning system, ...

WPI researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict ...

Integrating deep learning with traditional forecasting techniques can improve early warning systems by capitalizing on each approach’s respective advantages.

Researchers used AI and deep learning to find a link between brain structure and navigation skills but found no measurable ...

Of 372 patients studied, 79.3% and 20.7% were in the completion group and the non-completion group, respectively. The final BERT model achieved average F1 scores of 0.91 and 0.98 for time to ...