{"url":"/dataset/covidx","name":"COVIDx","full_name":"COVIDx CRX-2","description_markdown":"An open access benchmark dataset comprising of 13,975 CXR images across 13,870 patient cases, with the largest number of publicly available COVID-19 positive cases to the best of the authors' knowledge.\r\n\r\nSource: [COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images](/paper/covid-net-a-tailored-deep-convolutional)","description_withheld":null,"homepage":"https://github.com/lindawangg/COVID-Net","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/covid-net-a-tailored-deep-convolutional","title":"COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images","first_author":"Linda Wang","url":null},"license":{"name":"Unknown","url":null},"modalities":[],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"},{"name":"COVID-19 Diagnosis","url":"/task/covid-19-detection","datasets_with_task":"/datasets/task/covid-19-detection"}],"languages":[],"variants":["COVIDx"],"data_loaders":[{"repo":"https://github.com/lindawangg/COVID-Net","url":"https://github.com/lindawangg/COVID-Net","frameworks":["tf"]}],"num_papers_in_archive":96,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/covid-19-diagnosis-on-covidx","task":"COVID-19 Diagnosis","dataset_variant":"COVIDx","rows":3,"metrics":["3-class test accuracy","AUC"],"first_row_in_archive_order":{"model":"Sanskar et al.","paper":"/paper/a-novel-approach-for-detecting-normal-covid","metrics":{"3-class test accuracy":"98.38"},"code_links":[{"title":"sanskar-hasija/COVID-19_Detection","url":"https://github.com/sanskar-hasija/COVID-19_Detection"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/a-novel-approach-for-detecting-normal-covid","title":"A Novel Approach for detecting Normal, COVID-19 and Pneumonia patient using only binary classifications from chest CT-Scans","date":"2022-03-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/covid-widenet-a-capsule-network-for-covid-19","title":"COVID-WideNet—A capsule network for COVID-19 detection","date":"2022-03-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/corona-nidaan-lightweight-deep-convolutional","title":"Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection","date":"2021-02-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}