Thursday, May 30, 2024

Machine learning models receive failing grades in diagnosing COVID-19

A team of researchers led by the University of Cambridge found that out of the more than 300 COVID-19 machine learning models described in scientific papers in 2020, none is suitable for detecting or diagnosing COVID-19 from standard medical imaging, due to biases, methodological flaws, lack of reproducibility, and “Frankenstein datasets”, reports Tech Xplore. “… any machine learning algorithm is only as good as the data it’s trained on,” said first author Dr. Michael Roberts from Cambridge’s Department of Applied Mathematics and Theoretical Physics.

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