Skip to main content

AI being used to diagnose Alzheimer's disease early by reviewing brain scans

ai alzheimers italy diagnosis 42100086 l
Kacso Sandor/123RF
A devastating chronic neurodegenerative disease, Alzheimer’s disease (AD) currently affects around 5.5 million people in the United States alone. Causing progressive mental deterioration, it ultimately advances to impact basic bodily functions such as walking and swallowing.

Looking for a way to help, researchers at the University of Bari and Istituto Nazionale di Fisica Nucleare in Italy have developed new machine learning AI technology that may help identify Alzheimer’s a decade before doctors usually can, by way of non-invasive MRI brain scans. An early diagnosis — before any of the symptoms a doctor might recognize become apparent — could give patients a chance to make changes to their lifestyle which may slow Alzheimer’s progression.

Recommended Videos

“We used publicly available data, consisting of 67 brain MRI scans from the Alzheimer’s Disease Neuroimaging Initiative, including healthy controls and AD patients,” Nicola Amoroso, one of the lead researchers on the project, told Digital Trends. “We used this cohort to feed [our] artificial intelligence, then an independent test of about 148 subjects — including controls,

Alzheimer’s disease and mild cognitive impairment (MCI) subjects — was performed. According to our results, it is possible to distinguish a healthy brain from one with Alzheimer’s with an accuracy of 86 per cent. Crucially, it is also possible to detect the difference between healthy brains and those with MCI with an accuracy of 84 per cent.”

This isn’t the first similar study that involves using cutting-edge technology to help diagnose Alzheimer’s and other neurodegenerative diseases. Researchers at VU University Medical Centre in Amsterdam have also been using MRI scans to try and carry out similar early diagnosis of Alzheimer’s. Another intriguing high tech approach is one being taken at Cedars-Sinai Medical Center, University of Southern California (USC), and University of California, Los Angeles (UCLA), where researchers are working to develop an early diagnosis eye test for Alzheimer’s.

“Our goal is to use our approach for other pathologies,” Nicola Amoroso continued. “In particular, we are now investigating Parkinson’s disease, and preliminary results are really encouraging. It would be very important to support studies and clinical trials to let emerge novel preventive or disease modifying therapies.”

You can read a research paper on the University of Bari’s machine learning project here. With millions of people who could benefit from the research, they have our total support.

Luke Dormehl
Former Digital Trends Contributor
I'm a UK-based tech writer covering Cool Tech at Digital Trends. I've also written for Fast Company, Wired, the Guardian…
Range Rover’s first electric SUV has 48,000 pre-orders
Land Rover Range Rover Velar SVAutobiography Dynamic Edition

Range Rover, the brand made famous for its British-styled, luxury, all-terrain SUVs, is keen to show it means business about going electric.

And, according to the most recent investor presentation by parent company JLR, that’s all because Range Rover fans are showing the way. Not only was demand for Range Rover’s hybrid vehicles up 29% in the last six months, but customers are buying hybrids “as a stepping stone towards battery electric vehicles,” the company says.

Read more
BYD’s cheap EVs might remain out of Canada too
BYD Han

With Chinese-made electric vehicles facing stiff tariffs in both Europe and America, a stirring question for EV drivers has started to arise: Can the race to make EVs more affordable continue if the world leader is kept out of the race?

China’s BYD, recognized as a global leader in terms of affordability, had to backtrack on plans to reach the U.S. market after the Biden administration in May imposed 100% tariffs on EVs made in China.

Read more
Tesla posts exaggerate self-driving capacity, safety regulators say
Beta of Tesla's FSD in a car.

The National Highway Traffic Safety Administration (NHTSA) is concerned that Tesla’s use of social media and its website makes false promises about the automaker’s full-self driving (FSD) software.
The warning dates back from May, but was made public in an email to Tesla released on November 8.
The NHTSA opened an investigation in October into 2.4 million Tesla vehicles equipped with the FSD software, following three reported collisions and a fatal crash. The investigation centers on FSD’s ability to perform in “relatively common” reduced visibility conditions, such as sun glare, fog, and airborne dust.
In these instances, it appears that “the driver may not be aware that he or she is responsible” to make appropriate operational selections, or “fully understand” the nuances of the system, NHTSA said.
Meanwhile, “Tesla’s X (Twitter) account has reposted or endorsed postings that exhibit disengaged driver behavior,” Gregory Magno, the NHTSA’s vehicle defects chief investigator, wrote to Tesla in an email.
The postings, which included reposted YouTube videos, may encourage viewers to see FSD-supervised as a “Robotaxi” instead of a partially automated, driver-assist system that requires “persistent attention and intermittent intervention by the driver,” Magno said.
In one of a number of Tesla posts on X, the social media platform owned by Tesla CEO Elon Musk, a driver was seen using FSD to reach a hospital while undergoing a heart attack. In another post, a driver said he had used FSD for a 50-minute ride home. Meanwhile, third-party comments on the posts promoted the advantages of using FSD while under the influence of alcohol or when tired, NHTSA said.
Tesla’s official website also promotes conflicting messaging on the capabilities of the FSD software, the regulator said.
NHTSA has requested that Tesla revisit its communications to ensure its messaging remains consistent with FSD’s approved instructions, namely that the software provides only a driver assist/support system requiring drivers to remain vigilant and maintain constant readiness to intervene in driving.
Tesla last month unveiled the Cybercab, an autonomous-driving EV with no steering wheel or pedals. The vehicle has been promoted as a robotaxi, a self-driving vehicle operated as part of a ride-paying service, such as the one already offered by Alphabet-owned Waymo.
But Tesla’s self-driving technology has remained under the scrutiny of regulators. FSD relies on multiple onboard cameras to feed machine-learning models that, in turn, help the car make decisions based on what it sees.
Meanwhile, Waymo’s technology relies on premapped roads, sensors, cameras, radar, and lidar (a laser-light radar), which might be very costly, but has met the approval of safety regulators.

Read more