Autism is a spectrum of developmental disabilities impacting social skills, language processing, cognition and other functions. The UofL tool has been shown to be 98.5% accurate in diagnosing kids as young as two, which could give doctors more time to intervene with potentially life-changing therapy. Their results were published in the journal .

“Therapy could be the difference between an individual needing full-time care and being independent, holding a job and living a fulfilled life,” said Ayman El-Baz, a co-inventor and professor and chair in the . He developed the technology with Gregory Barnes and Manuel Casanova of the UofL .

shows therapy can have the most impact if done in early childhood, when the brain is more elastic. However, currently, and even fewer are diagnosed by age eight. The problem, the researchers say, is one of supply and demand — there are too many patients and too few specialists to conduct the interviews and examinations needed for diagnosis.

“As a result, there’s an urgent need for a new, objective technology that can help us diagnose kids early,” said Barnes, a professor of neurology and executive director of the . “We think our tool can help fill that need, while providing more objectivity over the current interview method.”

With the UofL technology, AI can make the initial diagnosis, which researchers think could reduce specialist workload by as much as 30%. The specialist would meet later with the patient to confirm the diagnosis and talk about next steps.

The UofL technology works by using AI to analyze magnetic resonance imaging (MRI) scans for differences and abnormal connections that may indicate autism. Tested against scans of 226 children between the ages of 24 and 48 months, the technology was able to identify the 120-some children with autism with near perfect accuracy.

By looking at the physical structures of the brain rather than using interviews, researchers believe they can make diagnoses more objective and target the specific parts of the brain that may benefit most from therapy.

“The idea is that by drawing from both medicine and engineering, we can come up with a better solution that improves lives,” said Mohamed Khudri, a undergraduate student and author on the paper.

The diagnostic technology and intellectual property received support through . That includes the office’s suite of innovation programs, aimed at developing research-backed inventions for market, including the prestigious national Innovation Corps (I-Corps) program through the National Science Foundation. UofL is one of only a handful of universities nationwide to have each of these programs — and it’s the only one to have them all.

He and 167 other inventors from institutions around the world will be formally recognized as 2019 NAI Fellows at a ceremony in Phoenix, Arizona, in April 2020, according to a .

“It is a great honor for me to be one of the NAI fellows,” said El-Baz, a UofL J.B. Speed School of Engineering alum and chair of bioengineering.

At UofL, El-Baz works at the intersection of computer science and medicine. Many of his inventions use artificial intelligence to analyze medical images, allowing them to very accurately diagnose everything from ��to to .

El-Baz is the sixth UofL inventor to be inducted into the NAI, following Suzanne Ildstad and Kevin Walsh (2014); William Pierce (2015); Paula Bates (2016); and most recently, Robert S. Keynton (2017).

“We’re very proud of Ayman, and all past UofL inductees, for this huge accomplishment and all the hard work behind it,” said Allen Morris, executive director of the . His office works with UofL researchers, like , to commercialize their inventions.��

“This kind of honor shows our university’s commitment to and leadership in research, invention and technology commercialization,” he said. “These inventions have the power to change and improve the way we work and live.”

Aside from the EPI-Center, El-Baz has also worked with other UofL programs for technology development and commercialization. He was the first researcher to hit a “trifecta” with UofL’s suite of��, having earned entry into the UofL Coulter Translational Partnership, NSF I-Corps and NSF AWARE:ACCESS programs.

“These crucial support mechanisms have enabled me to develop and translate technologies from ideation to commercialization quickly,” El-Baz said.

To date, El-Baz holds eight patents, five copyrights and has had 11 technologies optioned and two have been licensed to companies for further development and commercialization. Some technologies have also resulted in startup ventures like Autism Diagnostics Technologies Inc., which El-Baz co-founded, creating jobs and economic development.��

NAI fellows hold a collective 41,500 issued U.S. patents, resulting in 11,000 licensed technologies and companies, generating more than 36 million jobs and $1.6 trillion in revenue, according to the release.

“I am so impressed by the caliber of this year’s class of NAI Fellows, all of whom are highly-regarded in their respective fields,” NAI President Paul R. Sanberg said in the release. “The breadth and scope of their discovery is truly staggering. I’m excited not only see their work continue, but also to see their knowledge influence a new era of science, technology, and innovation worldwide.”