For two decades, a Georgia Tech professor has used simple data to track the best teams in college basketball and predict who ...

Machine learning analysis reveals which metrics drive March Madness seeding and predictive analytics in committee decisions.

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational ...

Among the primary concerns surrounding artificial intelligence is its tendency to yield erroneous information when ...

In large retail operations, category management teams spend significant time deciding which product goes onto which shelf and ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...

Abstract: Wireless Sensor Networks (WSNs) deployed in wilderness for natural disaster prevention face challenges due to the limited energy of sensor nodes, which restricts network performance and ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

Following a 4-0 start to the season, there appeared to be no stopping the Buffalo Bills in their quest to earn another AFC East title and the No. 1 seed in the AFC. The Bills (4-2) were averaging over ...

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer, with EGFR mutations serving as key oncogenic drivers. However, patients harboring EGFR mutations exhibit ...