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AI Developed To Detect Alzheimer’s A Decade Before The Symptoms Are Visible
Here is how to spot alzheimer's a decade before the symptoms even appear.
There are plenty of researchers working on to find out the best way to detect alzheimer's disease at the earliest.
Working towards this effect, recently a team of researchers from the University of Bari in Italy, have developed an algorithm using artificial intelligence (AI) that can spot tiny structural changes in the brain caused by the disease a decade before the symptoms even appear.
During the study, researchers trained their AI by feeding it 67 MRI scans - 38 from Alzheimer's patients and 29 from healthy controls. The researchers divided the scans into small regions and had their AI analyze the neuronal connectivity between. Then the algorithm was tested on another 148 people.

Out of the total number, 48 were scans of people with the disease, while 48 were scans of people who suffered from mild cognitive impairment and eventually developed full-blown Alzheimer's.
The AI algorithm could figure out which brains were healthy and which were not with 86 per cent accuracy.
What is Alzheimer's Disease?
Alzheimer's is a chronic and progressive neuro-degenerative disease that worsens over time. However, till date the cause of alzheimer's is hardly understood.
It has been found that about 70% of the alzheimer's cases are genetic. Other major risk factors are depression, hypertension and a history of head injuries.
For those suffering from alzheimer's, the brain cell connections and the cells themselves degenerate and die. This in the long run destroys the memory and other important mental functions.
All the treatment methods that are available can help slow the progress of the disease but the condition cannot be totally cured.

Signs & Symptoms of Alzheimer's Disease:
- Short-term memory loss
- Confusion
- Difficulty in concentrating
- Mood swings
- Irritation
- Restlessness
- Loss of appetite
- Depression
- Hallucination
- Anger
- Feeling of loneliness
- Change in personality



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