Hyderabad: At a time when the world is grappling with the coronavirus crisis, Researchers from New York-based Mount Sinai Health System have combined artificial intelligence, imaging and clinical data to rapidly detect COVID-19 in patients.
The algorithm can detect a COVID-19 case based on how lung disease looks in CT scans of a patient’s chest and data on the patient’s symptoms, age, bloodwork and possible contact with the virus. The team created the algorithm using CT scan data from coronavirus patients in Chinese medical centres.
It was found to be just as accurate as experienced radiologists and sometimes better in cases with no clear sign of lung disease in CT scans.
In a study published this week in Nature Medicine, researchers used AI algorithms in conjunction with chest CT scans and patient history to quickly diagnose patients who were positive for COVID-19 and improve the detection of patients who presented with normal CT scans.
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Dr Zahi Fayad, director of the BioMedical Engineering and Imaging Institute at the Icahn School of Medicine at Mount Sinai, said in a statement that AI has huge potential for analyzing large amounts of data quickly, an attribute that can have a big impact in a situation such as a pandemic.
"At Mount Sinai, we recognized this early and were able to mobilize the expertise of our faculty and our international collaborations to work on implementing a novel AI model using CT data from coronavirus patients in Chinese medical centres. We were able to show that the AI model was as accurate as an experienced radiologist in diagnosing the disease, and even better in some cases where there was no clear sign of lung disease on CT," said Fayad.
To develop the algorithm, the team used scans from 900 patients. These patients were admitted to 18 medical centres in 13 Chinese provinces between January 7 and March 3, 2020.
According to the data, 419 of the patients were confirmed COVID-19 positive cases and 486 patients were COVID-19 negative.
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Researchers also had the patient’s clinical information including blood test results that showed abnormalities in white blood cell counts or lymphocyte counts, age, sex and symptoms. They focused on CT scans and blood tests because doctors in China used those tests to diagnose COVID-19 cases.
"In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist," researchers wrote.
Researchers have increasingly relied on AI to diagnose and treat patients with the novel coronavirus.
In March, cognitive computing platform vendor behold.ai announced it had developed an AI-based algorithm to flag chest X-rays from COVID-19.
The algorithm mimics the workflow that a physician uses to diagnose COVID-19 to predict a positive or negative diagnosis. It produces separate probabilities of COVID-19 diagnosis based on CT images and clinical data.
It is to be noted that Mount Sinai researchers say their next steps will be to further develop the model to forecast patient outcomes and to share their results with other healthcare facilities.
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