Modern video coding architectures are at the forefront of addressing the increasing demands for efficient data compression, high-resolution broadcasting, and real-time processing in a global ...

Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of ...

Google DeepMind’s AI systems have taken big scientific strides in recent years — from predicting the 3D structures of almost every known protein in the universe to forecasting weather more accurately ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

Reed–Solomon codes have long been celebrated for their robust error-correction capabilities in digital communications and data storage. Decoding algorithms for these codes continue to evolve, aiming ...

The Agent-R1 framework provides a path to building more autonomous agents that can reason and use tools in unpredictable, ...

In the field of computer science, there is perhaps no more fundamental task than to sort. Bubble, heap, merge—take your pick. The methods for reordering data inside a computer have been theorized to ...

Objectives:Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the ...

A cohort of patients with incident breast, colorectal, and lung cancer were randomly distributed into six groups. The algorithm was iteratively modified, and the performance was assessed until no ...