Hi Sigma, do I have the Coronavirus?: Call for a New Artificial Intelligence Approach to Support Health Care Professionals Dealing With The COVID-19 Pandemic

TL;DR

This paper proposes a novel open collective AI approach using transfer learning on cough audio data to support COVID-19 diagnosis and healthcare decision-making, emphasizing data sharing and real-time collaboration.

Contribution

It introduces an open, large-scale, real-time AI framework for COVID-19 detection using cough recordings, contrasting with traditional private datasets and static approaches.

Findings

Transfer learning on cough audio achieves preliminary COVID-19 detection.

Plans for clinical validation in multiple countries are underway.

Advocates for crowdsourcing and data sharing in pandemic AI efforts.

Abstract

Just like your phone can detect what song is playing in crowded spaces, we show that Artificial Intelligence transfer learning algorithms trained on cough phone recordings results in diagnostic tests for COVID-19. To gain adoption by the health care community, we plan to validate our results in a clinical trial and three other venues in Mexico, Spain and the USA . However, if we had data from other on-going clinical trials and volunteers, we may do much more. For example, for confirmed stay-at-home COVID-19 patients, a longitudinal audio test could be developed to determine contact-with-hospital recommendations, and for the most critical COVID-19 patients a success ratio forecast test, including patient clinical data, to prioritize ICU allocation. As a challenge to the engineering community and in the context of our clinical trial, the authors suggest distributing cough recordings daily, hoping other trials and crowdsourcing users will contribute more data. Previous approaches to complex AI tasks have either used a static dataset or were private efforts led by large corporations. All existing COVID-19 trials published also follow this paradigm. Instead, we suggest a novel open collective approach to large-scale real-time health care AI. We will be posting updates at https://opensigma.mit.edu. Our personal view is that our approach is the right one for large scale pandemics, and therefore is here to stay - will you join?