Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven ...

As cities around the world continue to expand and evolve, understanding the dynamics of the housing market becomes increasingly critical for urban planners, ...

Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate ...

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 ...

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 ...

Factoring out nucleotide-level mutation biases from antibody language models dramatically improves prediction of functional mutation effects while reducing computational cost by orders of magnitude.

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Krupchytskyi: Deep learning models can have hundreds of such layers and millions and trillions of parameters. With deep learning, humans don't explicitly program every connection between the ...

Deep learning is a branch of machine learning based on algorithms that try to model high-level abstract representations of data by using multiple processing layers with complex structures. One of the ...

An understanding of community resilience and risk analysis is vital when it comes to protecting civilians and infrastructure ...