SOFTWARE developed by a University of Dayton Research Institute scientist to quickly diagnose COVID-19 has been exclusively licensed by Greenville, South Carolina, software development company Blue Eye Soft. The technology, which detected the presence of the COVID-19 disease on a dataset of chest X-rays in seconds with 98 percent accuracy, was adapted from existing medical diagnostic software in a matter of hours, then licensed in less than three days.
Blue Eye Soft owner Srikanth Kodeboyina — an alumnus of UD — and his team further developed the technology, and he plans to submit a full proposal to the FDA for approval within a matter of days. The company has already filed a provisional patent on the software.
“We hope to be able to bring this new tool to market very quickly,” Kodeboyina said, adding that his start-up company’s staff of 40 employees has been virtually joined in the last several days by more than 100 professionals based in Singapore, India and across the US, all contributing their expertise in artificial intelligence, medical licensing, cybersecurity and other related fields, to help expedite the development of the product.
The software, developed by UDRI research scientist Barath Narayanan, uses a “deep learning” algorithm that searches for markings on X-rays that indicate the presence of COVID-19. Narayanan, who spends his days working on sponsored research programs in artificial intelligence for manufacturing and other commercial applications, has for several years been working evenings and weekends pursuing his principal passion: advancing research in AI to help doctors diagnose and treat patients more quickly.
Using medical imaging including X-rays, CT scans, blood smear slides and eye scans, Narayanan had already developed a number of software codes that successfully detect—with 92 to 99 percent accuracy—lung and breast cancers, malaria, brain tumors, tuberculosis, diabetic retinopathy and pneumonia. When a set of chest X-rays from patients with and without COVID-19 were recently made available, Narayanan quickly switched focus to develop coding to detect the disease on the images. Drawing on expertise developed on and off the clock, he quickly developed an algorithm that classified the images as having, or not having, COVID-19 with a high degree of accuracy.
Narayanan, who received his master’s and doctoral degrees in electrical engineering from UD, said he enjoyed the image processing aspect of his graduate student research, and decided to use the field to help people in some way.
“I wanted to do something for the common good, and medical imaging seemed a good way to do that,” he said. “Software-based diagnostic tools can serve as a valuable, virtual second opinion for medical professionals, especially in parts of the world where medical teams are short-staffed. With additional research, these technologies can be fine-tuned to detect even the slightest anomalies on images—those that are difficult to see with the human eye—helping doctors diagnose and treat patients more quickly.”
Kodeboyina, who received his master’s degree in electrical and computer engineering from UD in 2011, has also been on a mission to develop software that will enhance human life, he said.
“I launched Blue Eye Soft in 2017 with a mission to create job opportunities in areas that are innovative and impactful,” he said. “Right now one of the most pressing needs on the planet is addressing the COVID-19 crisis. Artificial intelligence can be an important solution to support the healthcare industry in its fight to mitigate the impact of the disease, and we are on the leading edge of developing that technology.”
BES brought in a third-party company to validate its new diagnostic system, and a number of customers in the public and private sectors are already prepared to adopt the technology once it has received FDA approval, Kodeboyina said. In the United States, end-users will include hospitals, laboratories and medical professionals, he added.
UD vice president for research John Leland said the University has been working to execute technology licenses quickly, but completing an agreement between UD and BES in only two and a half days was unprecedented.
“We were driven to help Blue Eye Soft make this technology available as quickly as possible,” Leland said. “We are also excited that a UD grad has licensed one of our technologies and is working diligently to provide medical professionals a new tool in the fight against the spread of this devastating disease.”
While Narayanan is hoping to find funding that will enable him to further develop AI tools for the medical field, he said he will continue to work on his own time to help bring them to the healthcare industry. He credits his graduate advisor Russell Hardie, professor of electrical and computer engineering in the University’s School of Engineering, with ongoing guidance and support in his off-hours pursuits. – UNIVERSITY OF DAYTON RESEARCH INSTITUTE