Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for Amplifying the Signal While Reducing the Noise

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Most studies introducing AI models for COVID-19 diagnosis and prognostication exhibit systematic errors that make them unusable in most clinical settings. However, there remain opportunities for machine learning to assist front-line workers during the COVID-19 pandemic, and the steps we take now will leave us better in the future.