AI Algorithm-Based Test Can Speed Up COVID-19 Testing Eightfold and Locate Asymptomatic Carriers

A team of researchers are using artificial intelligence (AI) to develop an algorithm-based test that can speed COVID-19 testing eightfold and help locate asymptomatic carriers. The research team from the Ben-Gurion University of the Negev’s (BGU; Beersheba, Israel) Shraga Segal Department of Microbiology, Immunology and Genetics and the National Institute of Biotechnology, Soroka University Medical Center’s Virology Lab, and the Open University’s Department of Computer Science is using a laboratory robot to conduct the tests.

BGU has launched the BGU Coronavirus (COVID-19) Task Force to harness the University's brainpower and ingenuity to help cope with the coronavirus pandemic and has decided to set aside resources to bring the most promising projects to fruition. BGU has scientific experts, accomplished researchers, and accumulated institutional expertise spread across the University and housed in various departments. The Task Force will consolidate the University’s resources and leverage its excellent and close collaborative ties with key stakeholders from the realm of public health


“The initial results are very promising, and we are validating the method. Experience shows us that the way to slow down the spread of the pandemic is to increase the number of tests and break the chain of infection,” said Prof. Angel Porgador who is a part of the research team. “Our method should enable a widespread operation in the near future to detect the virus in the general population, which is not quarantined, but which could threaten the public more than the patients currently under observation.”

“In light of the mounting evidence of the importance of asymptomatic carriers in spreading COVID-19, it is critical to locate these carriers as quickly as possible, to isolate them and thus slow the infection rate in high-risk groups. We believe that our method will help do so by dramatically speeding up testing,” said Dr. Tomer Hertz who is also a part of the research team.

The researchers have determined that the key is to divide the samples into different pools. “The planning and constructing of the pools and the way we mix the individual samples enables us to identify and follow up with those found positive for COVID-19 after far fewer tests than the norm,” explained Dr. Noam Shental from the Open University’s Department of Computer Science.

“The next stage of the experiment is to test the medical services personnel at Soroka hospital in conjunction with the Infectious Disease Unit headed by Dr. Lior Nesher.”

“The sooner we can located asymptomatic carriers, the sooner we can return to a more normal life, so this innovation holds promising potential,” said Doug Seserman, chief executive officer of the New York City-based American Associates, Ben-Gurion University of the Negev. “We have a number of tests in development as a result of the fast mobilization of our researchers to address the pandemic.”

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Ben-Gurion University of the Negev