Researchers at Mount Sinai have developed an algorithm that can quickly detect COVID-19 based on how lungs appear in CT scans along with patient data such as age, sex, symptoms, bloodwork and potential contact with the virus. The algorithm imitates the workflow physicians use to diagnose COVID-19 and delivers a positive or negative diagnosis.
Mount Sinai researchers conducted scans of more than 900 patients received from institutional collaborators at Chinese hospitals between Jan.17 and March 3. The study’s results suggested that the AI algorithm can analyze large amounts of data much faster than traditional methods, which carries a significant impact during the pandemic.
Read the full news release here.
More articles on artificial intelligence:
Mayo Clinic tests AI to map how coronavirus affects heart health
7 ways hospitals use robots during the pandemic
Elon Musk claims AI chip could ‘fix anything that’s wrong with the brain’
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
