andrewmvd/convid19-x-rays: papers linking to it

Kaggle · www.kaggle.com/datasets/andrewmvd/convid19-x-rays

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to andrewmvd/convid19-x-rays (https://www.kaggle.com/datasets/andrewmvd/convid19-x-rays), 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.

Key findings#

6 papers in the tracked journals link to the Kaggle dataset andrewmvd/convid19-x-rays in their Crossref records, the first in 2020; most of them (3) in 2021.
By category: AI (6); the journals with the most are Applied Intelligence (3), Neural Computing and Applications (1) and Cognitive Computation (1).

By year#

20202022

Papers linking to andrewmvd/convid19-x-rays by publication year
Year	Papers
2020	2
2021	3
2022	1

Journals#

Journals whose papers link to andrewmvd/convid19-x-rays most
Journal	Papers
Applied Intelligence	3
Neural Computing and Applications	1
Cognitive Computation	1
Expert Systems with Applications	1

Papers linking to andrewmvd/convid19-x-rays, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-08-20	Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices	Applied Intelligence	Sakshi Ahuja, Bijaya Ketan Panigrahi, Nilanjan Dey et al.	380	cites it
2020-11-27	An automatic approach based on CNN architecture to detect Covid-19 disease from chest X-ray images	Applied Intelligence	Swati Hira, Anita Bai, Sanchit Hira	111	cites it
2021-05-03	Determination of COVID-19 pneumonia based on generalized convolutional neural network model from chest X-ray images	Expert Systems with Applications	Adi Alhudhaif, Kemal Polat, Onur Karaman	98	cites it
2022-12-28	COVID-19 Detection: A Systematic Review of Machine and Deep Learning-Based Approaches Utilizing Chest X-Rays and CT Scans	Cognitive Computation	Kirti Raj Bhatele, Anand Jha, Devanshu Tiwari et al.	53	cites it
2021-01-06	Intelligent system for COVID-19 prognosis: a state-of-the-art survey	Applied Intelligence	Janmenjoy Nayak, Bighnaraj Naik, Paidi Dinesh et al.	51	cites it
2021-04-29	A novel augmented deep transfer learning for classification of COVID-19 and other thoracic diseases from X-rays	Neural Computing and Applications	Fouzia Altaf, Syed Mohammed Shamsul Islam, Naeem Khalid Janjua	37	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). andrewmvd/convid19-x-rays: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-andrewmvd-convid19-x-rays

@misc{scholar4ai-code-kaggle-andrewmvd-convid19-x-rays,
  author = {{Scholar4AI}},
  title = {andrewmvd/convid19-x-rays: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-andrewmvd-convid19-x-rays}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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