The research team trained an AI algorithm using clinical data to better triage patients in low-testing environments and identify the infection at the point of care, as standard screening methods often take up to 48 hours to produce a diagnosis.
Routine blood tests conducted during the patient’s arrival, blood gas results and vital signs were used to train the algorithm.
The AI model used for diagnosis among COVID-19-presenting patients in the emergency department resulted in 77 percent sensitivity and 96 percent specificity, while the model used for diagnosis among patients admitted with COVID-19 resulted in 77 percent sensitivity and 95 percent specificity. More than 99 percent of patients the algorithm diagnosed as negative were in fact free of the disease.
Ecditor’s note: This article was updated July 14 at 9:00 a.m. CDT.
More articles on artificial intelligence:
Harvard, Stanford researchers lead COVID-19 AI data initiative: 4 things to know
4 AI systems outperforming medical experts
How UC San Diego Health, AWS implemented an AI imaging algorithm to detect COVID-19 in 10 days
Becker’s 3rd Annual Fall Chief Pharmacy Officer Summit is the top tier event that the people leading the future of pharmacy convene. This 3-day event is built specifically for Chief Pharmacy Officers and senior pharmacy leaders. The sessions examine the workforce, financial and clinical priorities shaping pharmacy today. Becker’s is where candid discussions flourish and new ideas thrive. Becker's 3rd Annual Fall Chief Pharmacy Officer Summit
