DualFluidNet: An Attention-Based Dual-Pipeline Network for Fluid Simulation

Physics, Fluid Physics, Information Science, Artificial Intelligence,
fluid simulation   learning physics   neural network   deep learning   point cloud transformation   SPH  

Background and Motivation Understanding fluid motion is crucial for comprehension of our environment and our interactions with it in the field of physics. However, traditional fluid simulation methods face limitations in practical applications due to high computational demands. In recent years, physics-driven neural networks have emerged as a promi...

Medical History Predicts Phenome-Wide Disease Onset and Enables the Rapid Response to Emerging Health Threats

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health,
medical history   disease prediction   rapid response   COVID-19   neural network   risk stratification  

Using Medical Records to Predict Common Disease Incidence and Support Rapid Response to Emerging Health Threats Research Background and Motivation The COVID-19 pandemic exposed systemic issues and a lack of data-driven guidance globally, significantly affecting the identification of high-risk populations and pandemic preparedness. Assessing individ...

Diffusion Model Optimization with Deep Learning

Diffusion Model Optimization with Deep Learning

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Biophysics,
deep learning   diffusion model   neural network   microstructural imaging   self-supervised learning  

Dimond: A Study on Optimizing Diffusion Models through Deep Learning Academic Background In brain science and clinical applications, Diffusion Magnetic Resonance Imaging (dMRI) is an essential tool for non-invasively mapping the microstructure and neural connectivity of brain tissue. However, accurately estimating parameters of the diffusion signal...