--- title: "agchung/Figure1-COVID-chestxray-dataset: papers citing it" description: "7 papers in the tracked journals link to the GitHub repository agchung/Figure1-COVID-chestxray-dataset in their Crossref records, the first in 2020; most of them (5) in 2021." url: https://scholar4ai.com/code/github-agchung-figure1-covid-chestxray-dataset markdown_url: https://scholar4ai.com/code/github-agchung-figure1-covid-chestxray-dataset.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "7 papers in the tracked journals link to the GitHub repository agchung/Figure1-COVID-chestxray-dataset in their Crossref records, the first in 2020; most of them (5) in 2021. (as of 2026-11-03)" data_url: https://scholar4ai.com/data/rankings.json updated: 2026-11-03T14:43:26+09:00 window: 2026-10-05 to 2026-11-03 source: OpenAlex (CC0) --- # agchung/Figure1-COVID-chestxray-dataset: papers linking to it Research papers in the 480 tracked journals that link to agchung/Figure1-COVID-chestxray-dataset (https://github.com/agchung/Figure1-COVID-chestxray-dataset), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from. - GitHub - 36 stars - 25 forks - created 2020 - https://github.com/agchung/Figure1-COVID-chestxray-dataset All repositories: https://scholar4ai.com/code.md ## Key findings - 7 papers in the tracked journals link to the GitHub repository agchung/Figure1-COVID-chestxray-dataset in their Crossref records, the first in 2020; most of them (5) in 2021. - By category: AI (6) and Information Systems (1); the journals with the most are Applied Intelligence (2), Pattern Recognition (1) and Cognitive Computation (1). ## By year *Papers linking to agchung/Figure1-COVID-chestxray-dataset by publication year* | Year | Papers | |---|---:| | 2020 | 1 | | 2021 | 5 | | 2022 | 1 | ## Journals *Journals whose papers link to agchung/Figure1-COVID-chestxray-dataset most* | Journal | Papers | |---|---:| | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 2 | | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 | | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 | | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 | | [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | 1 | ## Papers *Papers linking to agchung/Figure1-COVID-chestxray-dataset, most cited first* | Published | Title | Journal | Authors | Citations | Link | |---|---|---|---|---:|---| | 2021-01-29 | [A survey on generative adversarial networks for imbalance problems in computer vision tasks](https://doi.org/10.1186/s40537-021-00414-0) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Vignesh Sampath, Iñaki Maurtua, Juan José Aguilar Martín et al. | 262 | cites it | | 2020-09-21 | [OptCoNet: an optimized convolutional neural network for an automatic diagnosis of COVID-19](https://doi.org/10.1007/s10489-020-01904-z) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Tripti Goel, R. Murugan, Seyedali Mirjalili et al. | 178 | cites it | | 2021-08-25 | [SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network](https://doi.org/10.1016/j.patcog.2021.108255) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Aayush Kumar, Ayush R Tripathi, Suresh Chandra Satapathy et al. | 123 | cites it | | 2021-01-08 | [COVIDScreen: explainable deep learning framework for differential diagnosis of COVID-19 using chest X-rays](https://doi.org/10.1007/s00521-020-05636-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Rajeev Kumar Singh, Rohan Pandey, Rishie Nandhan Babu | 110 | cites it | | 2021-01-06 | [Intelligent system for COVID-19 prognosis: a state-of-the-art survey](https://doi.org/10.1007/s10489-020-02102-7) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Janmenjoy Nayak, Bighnaraj Naik, Paidi Dinesh et al. | 51 | cites it | | 2021-03-02 | [Deep Learning–Driven Automated Detection of COVID-19 from Radiography Images: a Comparative Analysis](https://doi.org/10.1007/s12559-020-09779-5) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Sejuti Rahman, Sujan Chandra Sarker, Md Abdullah Al Miraj et al. | 48 | cites it | | 2022-07-19 | [A Review Study of the Deep Learning Techniques used for the Classification of Chest Radiological Images for COVID-19 Diagnosis](https://doi.org/10.1016/j.jjimei.2022.100100) | [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | Yu Wang, Carol Anne Hargreaves | 17 | cites it | ## How this is measured Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month. ## Cite this page Scholar4AI. (2026). agchung/Figure1-COVID-chestxray-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-agchung-figure1-covid-chestxray-dataset ```bibtex @misc{scholar4ai-code-github-agchung-figure1-covid-chestxray-dataset, author = {{Scholar4AI}}, title = {agchung/Figure1-COVID-chestxray-dataset: papers linking to it}, year = {2026}, howpublished = {\url{https://scholar4ai.com/code/github-agchung-figure1-covid-chestxray-dataset}}, urldate = {2026-11-03}, note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0} } ``` License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).