Iranian Deputy Health Minister Iraj Harirchi announced on Tuesday that the country’s researchers have developed a cell phone software which helps people to avoid traffic in places potentially contaminated with COVID-19 virus.
“A major measure adopted with the help of Sharif University of Technology is identification of people infected with COVID-19 virus and the places they have trafficked by using a cell phone software,” Harirchi said.
“People can find places that the infected people have been to by the software,” he added.
Earlier this month, Iran unveiled homegrown smart software that helps physicians diagnose the novel coronavirus pneumonia (COVID-19) with the help of artificial intelligence that is used to analyze computed tomography (CT) scans.
The Iranian software was unveiled in a ceremony attended by Vice-President for Science and Technology Sorena Satatri and director of the Coronavirus Fight National Headquarters, Alireza Zali.
In comments at the event, Hamidreza Rabiee, professor of AI technologies at Sharif University of Technology, said the software has been developed in a joint project involving researchers from various Iranian universities in only one month.
The professor said the homegrown software’s error margin in detection of COVID-19 is much lower than the similar ones developed by China and Stanford University of the US.
He explained that medical centers can send online CT scans of lungs of suspicious cases to the researchers and immediately receive the results with high accuracy, noting that the software could also be installed on systems of local medical centers.
Computed tomography medical imaging is used in detecting the abnormalities in the patients’ lungs. In the images, many early coronavirus patients have single or multiple small patchy ground-glass opacities and interlobular septal thickening. The number and area of disease foci grow as the disease progresses, according to Imaging Technology News.
In the early days of the outbreak, radiological imaging was not regarded as a way to confirm evidence for COVID-19 cases, instead relying on a positive result of the PCR nucleic test. The supply of the PCR test kits, however, was limited and it took a long time to get the results after collecting the specimen. Many suspected patients had to wait to be tested to confirm their infection.
Inclusion of radiological findings in confirming COVID-19 diagnosis instantly increased the workload of the already hectic radiologists and physicians, who had to visually go through up to 300 images of a patient. Human efficiency and accuracy along with the risky physical contact in the exam process are gravely challenged. This was exactly the kind of situation where AI’s strengths find its ways and liberate the medical staff for more intimate care for the patients where human presence and interventions are indispensable and invaluable.
AI may help with both the exam process and reading of the images taken. As its more valued application, AI with a deep learning algorithm has proven to be a powerful aid in recognizing the lesions in CT images and even quantitatively characterizing the findings and comparing changes between exams, which works at a considerably greater speed and accuracy.
An algorithm may even help differentiate COVID-19 from a regular viral pneumonia. When a CT image suspicious of COVID-19 is detected, the AI alerts the physician and brings the case to the top of the physician’s work list, suggests possible infection, and recommends preset interventions according to the findings.