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AI applications in neurological diagnostics

Overview

Researchers are increasingly applying artificial intelligence to improve the diagnosis and monitoring of neurological conditions. In the United States, scientists have developed deep-learning systems to map brain aging and dementia risk. At the University of Southern California, a system led by Associate Professor Andrei Irimia uses MRI scans to identify specific brain regions that age at different rates. Additionally, researchers from the University of California, San Francisco, and Beth Israel Deaconess Medical Center have developed a machine-learning model that analyzes EEG recordings during sleep. By examining microscopic characteristics of brain waves, the system calculates a ‘brain age’. Findings indicate that a 10-year gap between estimated brain age and chronological age correlates with a nearly 40 percent increase in dementia risk.

Further advancements include the development of a system using a model called SigLIP, which combines brain MRI images with clinical data. In a study of 416 individuals, this method achieved an AUC of 0.91 for predicting the risk of progression to Alzheimer’s disease over a four-year period. New research from Harvard Medical School suggests that tracking gray matter shrinkage via routine MRI scans may help predict the progression speed of early-onset Alzheimer’s. In the Czech Republic, AI tools have demonstrated high reliability in monitoring multiple sclerosis activity.

Expanding on these predictive capabilities, the EU-funded AI-Mind project is developing AI tools to identify individuals at high risk of dementia before clinical symptoms manifest. Led by researchers such as Vebjørn Andersson and neurologist Ira Haraldsen at Oslo University Hospital, the project aims to facilitate earlier monitoring and intervention. Meanwhile, in England, experts at the Alzheimer’s Society are calling for a major overhaul of dementia care, proposing a target for patients to receive a precise diagnosis within 18 weeks of seeing a GP to address current delays that average 3.5 years.

Entities

Oslo University Hospital · University of Ostrava · Andrei Irimia · University of California, San Francisco · Ostrava University Hospital

Timeline

  1. [HEALTH] 2 sources
    AI tools developed to improve early dementia detection

    Researchers are developing AI tools through the EU-funded AI-Mind project to detect dementia risk earlier, aiming to provide support before significant clinical symptoms appear.

  2. [HEALTH] 4 sources
    Dementia care: New diagnosis targets and AI diagnostic tools

    Experts propose an 18-week dementia diagnosis target for the NHS, while EU-funded researchers develop AI tools to identify at-risk individuals before clinical symptoms emerge.

  3. [HEALTH] 3 sources
    AI and biomarkers advance neurological disease prediction and diagnosis

    New medical studies show AI and biomarkers are improving the early prediction of Parkinson's, the identification of migraine subtypes, and the understanding of neuroprotective factors in Multiple Sclerosis.

  4. [HEALTH] 2 sources
    Medical research identifies new indicators for Alzheimer’s and dementia risk

    Recent studies highlight new ways to assess dementia risk, including using MRI scans to track brain shrinkage and measuring arterial stiffness to predict cognitive decline in older adults.

  5. [HEALTH] 3 sources
    AI tool improves multiple sclerosis detection in MRI scans

    A study by Czech researchers shows AI can detect multiple sclerosis lesions on MRI scans with 91.8% accuracy, assisting doctors in monitoring disease activity.

  6. [TECHNOLOGY] 3 sources
    AI system shows promise in early Alzheimer's risk detection

    An AI system using SigLIP can combine MRI scans and clinical data to predict Alzheimer's progression risk with high accuracy, potentially aiding early detection.

  7. [HEALTH] 2 sources
    AI assists in detecting multiple sclerosis activity

    A study by Czech researchers shows AI matches radiologist accuracy by 91.8 percent in assessing multiple sclerosis activity via MRI scans, aiding in the precise tracking of disease progression.

  8. [HEALTH] 2 sources
    AI models developed to map brain aging and dementia risk

    New AI models are being developed to map brain aging through MRI scans and EEG sleep data, offering more precise ways to identify regional aging and predict dementia risk.

Sources

ad-hoc-news.de · bedaromano.blog.ilsole24ore.com · cyprus-mail.com · dailymail.co.uk · de.euronews.com · doctorulzilei.ro · fehmarn24.de · go4it.ro · hameensanomat.fi · iNews.co.uk · japantimes.co.jp · jcted.cz · knowridge.com · kraj-jihocesky.cz · ksml.fi · newsai.ro · prozeny.cz · psypost.org · sciencemag.cz · wonderfulengineering.com

This summary has been updated 5 times: see revision history