{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/covidx-us-an-open-access-benchmark-dataset-of","title":"COVIDx-US -- An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analytics","arxiv_id":"2103.10003","date":"2021-03-18","proceeding":null,"authors":["Ashkan Ebadi","Pengcheng Xi","Alexander MacLean","Stéphane Tremblay","Sonny Kohli","Alexander Wong"],"abstract":"The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. Apart from the global health crises, the pandemic has also caused significant economic and financial difficulties and socio-physiological implications. Effective screening, triage, treatment planning, and prognostication of outcome plays a key role in controlling the pandemic. Recent studies have highlighted the role of point-of-care ultrasound imaging for COVID-19 screening and prognosis, particularly given that it is non-invasive, globally available, and easy-to-sanitize. Motivated by these attributes and the promise of artificial intelligence tools to aid clinicians, we introduce COVIDx-US, an open-access benchmark dataset of COVID-19 related ultrasound imaging data. The COVIDx-US dataset was curated from multiple sources and its current version, i.e., v1.2., consists of 150 lung ultrasound videos and 12,943 processed images of patients infected with COVID-19 infection, non-COVID-19 infection, other lung diseases/conditions, as well as normal control cases. The COVIDx-US is the largest open-access fully-curated dataset of its kind that has been systematically curated, processed, and validated specifically for the purpose of building and evaluating artificial intelligence algorithms and models.","url_abs":"https://arxiv.org/abs/2103.10003v2","url_pdf":"https://arxiv.org/pdf/2103.10003v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"covidx-us-an-open-access-benchmark-dataset-of","repo_url":"https://github.com/nrc-cnrc/COVID-US","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"covidx-us-an-open-access-benchmark-dataset-of","repo_url":"https://github.com/guojiaqi-1020/medivlad","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"covidx-us-an-open-access-benchmark-dataset-of","repo_url":"https://github.com/maclean-alexander/COVID-Net-US","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"prognosis","task_name":"Prognosis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2103.10003","atlas_url":"https://app.syntology.ai/?focus=2103.10003","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}