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Responds quickly to recent changes: By focusing on the last N observations, a moving average makes the score highly sensitive to new behavior. If a normally low-risk customer suddenly starts making ...
The company trained GLM-4.5 through a multistep workflow. First, it developed an initial version of the model using a dataset ...
Scientists often seek new materials derived from polymers. Rather than starting a polymer search from scratch, they save time ...
This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in ...
New AI technology can spot breast cancer in MRI scans more accurately than current digital methods, while also pinpointing ...
Four previously tested AI diagnostic algorithms for skin cancer demonstrated lower sensitivity and specificity when tested on ...
NewYork-Presbyterian researchers have developed a deep learning model that increases doctors' abilities to diagnose ...
With the development of convolutional neural networks, the scale of activation data has increased dramatically, posing significant challenges to model storage and computation. The insight indicates ...
We propose an improved imperialist competitive algorithm (I-ICA)-based extraction method for small-signal model of GaN HEMT on Si. The proposed algorithm introduces differential evolution and boundary ...
ObjectiveThis study aimed to construct a machine learning predictive model for prognostic analysis of patients with p- ARDS.MethodsIn this single-center retr ...
A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA ...