New brain scanning technology can detect early-stage Alzheimer’s with near 100% accuracy

A new machine-learning-based brain scan can detect with near-perfect accuracy when a person has Alzheimer’s disease, and researchers hope it will become available in the next few years.

Researchers at Imperial College London in England used an already existing algorithm to detect cancer tumors and used it to detect early Alzheimer’s with 98% accuracy.

By detecting Alzheimer’s disease early, treatment can begin sooner, doctors have more time to plan how to approach treatment, and the patient can still make plans for the future on their own with a healthy mind.

While the machine learning system is still in its infancy, the researchers hope it will be available to consumers in a few years.

“Currently, no other simple and widely available method can predict Alzheimer’s disease with this level of accuracy, so our research is a huge step forward,” said Professor Eric Aboagye, who led the study.

“Many patients presenting at memory clinics with Alzheimer’s also have other neurological disorders, but even within this group, our system was able to distinguish Alzheimer’s patients from those without.”

Publishing their findings this week in Communications Medicine, the researchers collected data from 400 patients diagnosed with early or late-stage Alzheimer’s disease.

They used a machine learning system used to classify cancer tumors and used it in the brain instead.

The brain was divided into 115 regions, and more than 600 features such as the size, shape, and texture of each section had to be scanned.

Using an MRI machine already available in most hospitals in developed countries, doctors can scan a person’s brain that the machine learning system can read.

The system correctly identified a case of Alzheimer’s in 98% of participants’ brain scans.

In about 80% of the scans, she was able to tell whether the person had late-stage or early-stage Alzheimer’s.

“While neuroradiologists are already interpreting MRI scans to help diagnose Alzheimer’s, the scans likely have features that even experts can’t see,” he said. Paresh Malhotra is a neurologist at the university.

“Using an algorithm that can select the tissue and fine structural features of the brain affected by Alzheimer’s can really improve the information we can get from standard imaging techniques.”

There is currently no cure for Alzheimer’s disease, and treatments focus more on managing symptoms rather than stopping the progression of the disease.

Only one drug has so far been approved by regulators to halt the cognitive decline associated with Alzheimer’s disease: Biogen’s Aduhelm. The use of the drug is extremely limited, as many experts doubt that it works.

However, finding Alzheimer’s disease early is still valuable. Knowing that he will soon lose his memory, he better prepare himself for a life where everything is no longer there.

This involves creating a care situation, whether it’s a family member or some type of private nurse.

It also allows the person to put things in order after life without experiencing significant amnesia.

Researchers also hope that machine learning systems will aid future drug studies, as they can identify Alzheimer’s patients before other methods and then use them as study participants.

“Waiting for a diagnosis can be a terrifying experience for patients and their families. If we can reduce the time they have to wait, make the diagnosis easier, and reduce some of the uncertainty, that would help a lot,” he said.

“Our new approach can identify patients at an early stage for clinical trials of new drug treatments or lifestyle changes that are currently very difficult to do.”

More than six million Americans are living with Alzheimer’s, with Alzheimer’s being one of the biggest killers over 65, according to the Alzheimer’s Association.