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Test predicts dementia risk years earlier

An EEG test can identify dementia risk five to seven years before progression to mild cognitive impairment or Alzheimer’s dementia, new research suggests.
Using EEG data, which measures the brain’s electrical activity, from older adults with only subjective memory concerns, the longitudinal study found this non-invasive test can flag functional changes long before standard tools detect disease.
Researchers collected baseline resting EEG recordings from 88 older adults who had subjective cognitive impairment (self-reported decline without a clinical diagnosis of mild cognitive impairment, early memory problems or dementia).
The study was conducted by BrainScope, a commercial-stage neurotechnology company in Maryland, US, which applies artificial intelligence and computational neuroscience to brain electrical signals.
Participants then received annual clinical assessments and staging of cognitive decline. Over time, some progressed to mild cognitive impairment or dementia, while others remained cognitively normal.
Using BrainScope’s proprietary EEG-based biomarker platform, researchers identified distinct brain-activity patterns at the initial visit that accurately predicted future decline.
BrainScope’s EEG biomarker achieved an area under the curve (AUC) of 0.90, a measure of diagnostic accuracy, and performance was validated across independent international cohorts.
The findings suggest that with BrainScope’s signal processing and AI-enabled analytics, EEG could serve as a rapid, affordable and non-invasive assessment to identify Alzheimer’s-related brain dysfunction years before meaningful memory loss.
Early identification matters because by the time traditional imaging detects Alzheimer’s pathology, significant and often irreversible neurological damage may already have occurred.
Identifying risk earlier also fits a fast-evolving therapeutic landscape in which many disease-modifying therapies and prevention trials require people to be found years before conventional diagnosis.
Earlier awareness can help individuals and families pursue evidence-based lifestyle changes, proactive care planning and research participation, shifting care from reactive management to earlier intervention.
“The rapid evolution of Alzheimer’s therapeutics demands equally innovative biomarkers.” Howard Fillit, co-founder and chief science officer of the Alzheimer’s Drug Discovery Foundation, said.
“As the field moves towards more complex, combination therapy strategies and precision prevention, tools like BrainScope’s will play a critical role in early risk identification and enabling a tailored approach to treatment.” Fillit said.
Key funding for the biomarker’s development was provided by the Alzheimer’s Drug Discovery Foundation, whose early support BrainScope credits as instrumental in achieving this milestone.
The foundation has a longstanding record of advancing Alzheimer’s diagnostics, including early support for technologies such as the first amyloid PET scan and the first blood-based biomarker test for the disease.
“At BrainScope, our mission has always been to translate the brain’s electrical signals into clinically meaningful insights and build the platform that becomes the brain’s vital sign,” Matt Adams, chief executive of BrainScope, said.
“This publication in Scientific Reports validates years of research using EEG to detect functional brain changes in normal elderly with subjective cognitive complaints,” Leslie Prichep, chief scientific officer of BrainScope and first author of the study, said.
“The importance of identifying risk of future cognitive decline, long before structural damage occurs, can have significant impact on brain health in the elderly early enough to meaningfully change outcomes.”
BrainScope is expanding its AI-enabled EEG platform into new clinical indications, including neurodegenerative diseases and stroke.
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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