Key bits of the abstract (below the fold):<p>Abstract— Goal: We hypothesized that COVID-19 subjects,
especially including asymptomatics, could be accurately
discriminated only from a forced-cough cell phone recording using
Artificial Intelligence. To train our MIT Open Voice model we
built a data collection pipeline of COVID-19 cough recordings
through our website (opensigma.mit.edu) between April and May
2020 and created the largest audio COVID<p>....<p>Results: When validated with subjects diagnosed using an
official test, the model achieves COVID-19 sensitivity of 98.5%
with a specificity of 94.2% (AUC: 0.97). For asymptomatic
subjects it achieves sensitivity of 100% with a specificity of 83.2%.