A University of Michigan AI model diagnoses more than 50 brain disorders from MRI scans in seconds, with up to 97.5 percent accuracy.

Health & Wellness Design Assistant Professor Edlin Garcia, Ph.D., is co-principal investigator (PI) on a research project titled " Designing Accountable Mental Health Large Language Model Therapy ...

The Department of Energy's Oak Ridge National Laboratory has launched a novel robotic platform to rapidly analyze plant root systems as they grow, yielding AI-ready data to accelerate the development ...

This innovation leverages deep learning to generate realistic family member images based on user input, offering practical applications in personalized digital experiences, virtual storytelling, and ...

Abstract: Compared to natural images, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) exhibits lower spatial resolution, reduced contrast sensitivity, and limited detail visibility, ...

DeepSeek released its V3.2 model on Monday. It aims to keep accessible AI competitive for developers. V3.2 heats up the race between open and proprietary models. Chinese AI firm DeepSeek has made yet ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

data/ ├── noise/ # Background noise samples used for mixing ├── train/ # Training dataset │ ├── clean_trainset_wav/ # Clean training audio │ └── noisy_trainset_wav/ # Noisy training audio ├── validate ...

What if the future of research wasn’t just faster, but fundamentally smarter? Imagine a tool that could not only parse through dense datasets but also reason through complex problems, adapt to your ...

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...