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AI system could help identify Alzheimer’s earlier

An AI tool could help identify Alzheimer’s disease around two years earlier by analysing signals already recorded in patients’ clinical records.
DementAI, a prototype developed by consultancy Katalyze Data, analyses existing medical record data to flag patients who may show early signs of the condition but have not yet been referred for specialist assessment.
Built as an end-to-end working prototype, the system connects stages clinicians often manage separately, from analysing medical records to applying models within decision pathways.
It is designed to work using information healthcare providers already hold, turning fragmented data into actionable insight without adding new screening burdens.
The system combines structured medical records, brain activity data and unstructured clinical information, using synthetic data where appropriate to support development.
By blending these signals, it aims to detect subtle patterns of decline that may be difficult to identify during short consultations.
Tamás Bosznay, principal consultant at Katalyze Data, said: “We are in a race against time when it comes to dementia.
“Early identification can make a meaningful difference to how patients and families experience the condition.
“But without better ways of finding people sooner, those opportunities can be lost.
“We didn’t build DementAI just to make predictions; we built it to buy patients time.
“By surfacing the signals already hiding in plain sight within clinical records, the system is designed to help ensure that when care teams are ready to act, the right patients are identified earlier and more consistently.”
DementAI was developed as part of the SAS Hackathon 2025, where it won the healthcare and life sciences category.
The team is now seeking engagement with NHS trusts to explore pilot deployments that could validate the model’s impact and support efforts to reduce delays in diagnosis.
Dr Iain Brown, global head of AI and data science at SAS, said: “Synthetic data, agentic AI concepts and governance are not ‘nice-to-haves’ in sensitive settings like healthcare.
“They are what make innovation usable at scale.
“DementAI shows how artificial intelligence can be applied in a way that is both ambitious and responsible.
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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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