The American Journal of Managed Care

Model Aids IPF Diagnosis and Treatment in TCM

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
EurekAlert!

A new AI-based method advances solid oxide cell modeling by improving physical consistency and computational efficiency

Researchers from the University of Chinese Academy of Sciences and collaborating institutions have developed a novel ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...
Wired

Liquid AI Is Redesigning the Neural Network

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...
EurekAlert!

Physics-informed neural networks building blocks for Heston model (IMAGE)

It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model.  The market price of risk is taken to be λ=0. Automatic differentiation is ...
Semiconductor Engineering

Study Of HW Acceleration for Neural Networks (Arizona State Univ.)

A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...