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 ...

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

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 ...

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to ...

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.

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 ...

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

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...

As the electric vehicle (EV) market surges, the biggest anxiety for owners and manufacturers remains the battery. How long ...

One of the most puzzling aspects of common chronic inflammatory skin diseases such as psoriasis is how they become chronic. What allows an ongoing condition to stay dormant for months or even years, ...

The firm says it can can reduce the cost of chip development by more than 75% and cut the timeline by more than half.