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Using blood test data, AI can help laboratories detect Covid-19 infection probability

The AI software developed by the University of Vermont and Cedars-Sinai uses routine blood tests to predict the probability of COVID-19 infection.

Akarsh Verma | December 13, 2020 | Updated 17:39 IST

Highlights

  • Researchers from the University of Vermont and Cedars-Sinai have developed an AI model that can predict the probability of a patient being Covid-19 positive.
  • The AI model uses blood tests to predict the chances of Covid-19 infection with high accuracy.
  • The AI model could help hospitals utilise their scarce testing capabilities more efficiently.

Hospital-based laboratories and doctors at the front line of the Covid-19 pandemic might soon add a new arrow to the testing toolkit quiver, i.e. Artificial Intelligence. A recent study conducted by researchers from the University of Vermont in the US and Cedars-Sinai describes the performance of Biocogniv's new AI-COVID software. The research team found high accuracy in predicting the probability of Covid-19 infection using routine blood tests, which can help hospitals reduce the number of patients referred for scarce PCR testing.

"Nine months into this pandemic, we now have a better understanding of how to care for patients with Covid-19," said lead author and University of Vermont Assistant Professor Timothy Plante, M.D., M.H.S., "but there's still a big bottleneck in Covid-19 diagnosis with PCR testing." PCR testing is the current standard diagnostic for COVID-19, and requires specific sampling, like a nasal or throat swab, and specialised laboratory equipment to run.

Since both complete blood count and complete metabolic panels are common laboratory tests often ordered by the emergency departments to get an insight into other systems, the researchers were successful in training their AI model to analyse changes in these routine tests and assign a probability of the patient being Covid-19 negative with high accuracy.

Biocogniv Chief Operating Officer Tanya Kanigan, Ph.D., says, "According to data from over 100 US hospitals, the national average turnaround time for COVID-19 tests ordered in emergency rooms is above 24 hours, far from the targeted one-hour turnaround."

"AI-COVID takes seconds to generate its informative result once these blood tests return, which can then be incorporated by the laboratory into its test interpretation," says Jennifer Joe, M.D., an emergency physician in Boston, Mass. and Biocogniv's Chief Medical Officer. "In an efficient emergency department that prioritises these routine blood tests, the door-to-result time could be under an hour."

Biocogniv CEO Artur Adib, Ph.D., says, "I'm honoured to have such an impressive team of medical scientists from the University of Vermont and Cedars-Sinai as collaborators in validating this timely model. AI has progressed considerably; the time is now to leverage this powerful tool for new healthcare breakthroughs, and we're glad to direct it to help hospital laboratories and providers combat the current COVID-19 crisis."

The study has been published online in the Journal of Medical Internet Research and is available online at https://www.jmir.org/2020/12/e24048.

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