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Causal training of physics-informed neural networks

Methods, systems, and computer-readable media for causal training of physics-informed neural networks (PINNs). The shortcoming of conventional PINNs may be due to the inability of existing PINNs formulations to respect the spatio-temporal causal structure that is inherent to the evolution of physical systems. This is a fundamental limitation and a key source of error that ultimately steers FINN models to converge towards erroneous solutions. Methods can include a re-formulation of PINNs loss functions that can explicitly account for physical causality during model training. This modification alone is enough to introduce significant accuracy improvements, allowing us to tackle problems that have remained elusive to PINNs.

Published: 7/17/2025

MRI Scan Time Reduction Method Using Deep Learning

A reconstruction algorithm based on a generative diffusion model for multi-coil, highly undersampled non-Cartesian MRI allowing drastic reduction of scan time

Published: 8/1/2025

Machine-Learning Foundation Model For The Early Detection Of Neurodegenerative Diseases

A machine learning technique that identifies biomarkers from neuroimaging data, allowing for identification and treatment of populations vulnerable to neurodegenerative diseases.

Published: 1/17/2025

Dye-Loaded Micelles for Direct Visualization of Colorectal Cancer

A tissue-selective, biocompatible contrast agent enables the visual identification of tumors and tumor margins during procedures

Published: 1/8/2025

Human-AI Hybrid Intelligence Model to Accurately Recognize and Segment Organs on Medical Scans 70% Faster Than Physicians

AAR-DL (Automatic Anatomy Recognition – Deep Learning) is a hybrid intelligence recognition and delineation segmentation model that outputs automatically delineated organs in medical images by combining natural intelligence’s (i.e., human knowledge’s) and artificial intelligence's strengths to map organs and their boundaries in the given images.

Published: 8/7/2025

Revolutionizing CT Imaging: Gold Nanoparticles with Biodegradable Polymer Encapsulation

Innovative CT contrast agent using biodegradable polymer-encapsulated gold nanoparticles for enhanced imaging and safe excretion.

Published: 2/12/2024

Coherent Generation Of High-Dimensional Structured Light Using A Hyperdimensional Spin-Orbit Microlaser

The current invention describes next-generation high-capacity noise-resilient communication and computing technology. The invention describes a method to coherently generate high-dimensional structured light, including spin-orbit states, in an integrated and scalable way.

Published: 10/16/2023

Xenon Biosensors Improve Early Breast Cancer Detection

A nuclear magnetic resonance (NMR) based enzyme-detection system comprising xenon (129Xe) biosensors complexed with an enzyme-specific peptide substrate.

Published: 10/16/2023
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