AI can help detect different types of Parkinson’s disease

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Parkinson’s disease is a sickness that affects how people move and think. It can look and feel different in different people.

Some scientists wanted to know if they could use computers to figure out these differences better.

Computers and Pictures: A New Way to Look at Parkinson’s

Scientists from two big research places, the Francis Crick Institute and UCL Queen Square Institute of Neurology, worked with a tech company called Faculty AI.

They used computers to look at pictures of special cells that came from patients with Parkinson’s disease. These pictures helped the computer understand different types of Parkinson’s disease.

Until now, doctors had a hard time telling apart these types. This meant they couldn’t always give the best help to the patients.

By looking at how the disease acts in these cells, the scientists hoped to find better ways to help.

People get Parkinson’s when some proteins in their brain don’t work right, or when tiny power plants in their cells, called mitochondria, break.

Some people get Parkinson’s because of their family genes, but many get it for unknown reasons.

The scientists took special cells from patients and made them show signs of Parkinson’s. They then took very close-up pictures of these cells.

They taught a computer program to see the different types of Parkinson’s in these pictures. When they showed new pictures to the computer, it could tell the difference very well.

This is a big deal because it means doctors might one day use this to give better advice to patients.

James Evans, a student at the Crick and UCL, said that using computers let them see more details in their pictures.

Before, they could only see a few things, but now they can see many. This means they can understand the disease better.

What This Means for Patients and Doctors

Sonia Gandhi, a big boss of a research group at the Crick, talked about how this is helpful. She said that they know a lot about how Parkinson’s works in the brain.

But they don’t know exactly how it’s happening in each patient while they’re still alive. This means they can’t always give the best medicines.

She said, “We don’t have medicines that really slow down Parkinson’s right now.

By looking at cells that act like a patient’s brain cells, and taking lots of pictures, we made a computer program that can tell the difference between Parkinson’s types.

This is a strong way to find out the kind of Parkinson’s a person has while they are still alive.”

She also hopes that one day, they can test medicines on these special cells first. They can see if the medicine works before giving it to patients. This could change how they treat each patient in a special way, just for them.

James Fleming, who knows a lot about computers at the Crick and worked with Faculty AI, said computers are very powerful tools.

But sometimes, people make them sound too hard to understand. He was happy that even people who didn’t know much about computers could use them for this project. Now, they want to use computers for even more projects at the Crick.

What’s Next for This Research?

The scientists want to do more. They want to see if this computer method works for people with Parkinson’s who got it from their family genes. They also want to see if it works for people who got Parkinson’s but don’t know why.

In the end, the scientists are hopeful. They think that by using computers and pictures, they can find out more about Parkinson’s. This can help them give better care to people with this disease.

It’s a new way to understand a very old problem, and it might be a big step forward in helping people with Parkinson’s live better lives.

If you care about Alzheimer’s, please read studies about Vitamin D deficiency linked to Alzheimer’s, vascular dementia, and Oral cannabis extract may help reduce Alzheimer’s symptoms.

For more information about brain health, please see recent studies about Vitamin B9 deficiency linked to higher dementia risk, and results showing flavonoid-rich foods could improve survival in Parkinson’s disease.

The study was published in Nature Machine Intelligence.

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