rsna-pneumonia-detection-challenge: papers linking to it

Kaggle · www.kaggle.com/competitions/rsna-pneumonia-detection-challenge

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Research papers in the 480 tracked journals that link to rsna-pneumonia-detection-challenge (https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge), 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#

14 papers in the tracked journals link to the Kaggle dataset rsna-pneumonia-detection-challenge in their Crossref records, the first in 2020; most of them (7) in 2021.
By category: AI (14); the journals with the most are Neural Computing and Applications (4), Nature Machine Intelligence (3) and Applied Intelligence (2).
7 of the papers build on one another: a later paper cites an earlier one that also links rsna-pneumonia-detection-challenge.

By year#

20202026

Papers linking to rsna-pneumonia-detection-challenge by publication year
Year	Papers
2020	2
2021	7
2023	1
2024	1
2025	1
2026	2

Journals#

Journals whose papers link to rsna-pneumonia-detection-challenge most
Journal	Papers
Neural Computing and Applications	4
Nature Machine Intelligence	3
Applied Intelligence	2
Pattern Recognition	2
Cognitive Computation	2

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Automatically discriminating and localizing COVID-19 from community-acquired pneumonia on chest X-rays Pattern Recognition, 2020
- Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans Nature Machine Intelligence, 2021 — cites the paper above
  - GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays Pattern Recognition, 2021 — cites the paper above
    - Review on chest pathogies detection systems using deep learning techniques Artificial Intelligence Review, 2023 — cites the paper above
  - AI-driven techniques for thoracic disease classification in chest radiography: A comprehensive review and critical analysis Neural Computing and Applications, 2026 — cites the paper above
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks Applied Intelligence, 2020
- Deep Learning–Driven Automated Detection of COVID-19 from Radiography Images: a Comparative Analysis Cognitive Computation, 2021 — cites the paper above

Papers linking to rsna-pneumonia-detection-challenge, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-03-15	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans	Nature Machine Intelligence	Michael Roberts, Derek Driggs, Matthew Thorpe et al.	1,045	cites it
2021-05-31	AI for radiographic COVID-19 detection selects shortcuts over signal	Nature Machine Intelligence	Alex J. DeGrave, Joseph D. Janizek, Su‐In Lee	631	cites it
2020-10-17	Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks	Applied Intelligence	Narinder Singh Punn, Sonali Agarwal	218	cites it
2020-08-26	Automatically discriminating and localizing COVID-19 from community-acquired pneumonia on chest X-rays	Pattern Recognition	Zheng Wang, Ying Xiao, Yong Li et al.	186	cites it
2021-01-08	COVIDScreen: explainable deep learning framework for differential diagnosis of COVID-19 using chest X-rays	Neural Computing and Applications	Rajeev Kumar Singh, Rohan Pandey, Rishie Nandhan Babu	110	cites it
2025-01-13	Exploring scalable medical image encoders beyond text supervision	Nature Machine Intelligence	Fernando Pérez‐García, Harshita Sharma, Sam Bond-Taylor et al.	91	cites it
2021-02-02	Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection	Applied Intelligence	Mainak Chakraborty, Sunita Dhavale, Jitendra Ingole	56	cites it
2024-02-17	TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images	Cognitive Computation	Tawsifur Rahman, Amith Abdullah Khandakar, Ashiqur Rahman et al.	51	cites it
2021-03-02	Deep Learning–Driven Automated Detection of COVID-19 from Radiography Images: a Comparative Analysis	Cognitive Computation	Sejuti Rahman, Sujan Chandra Sarker, Md Abdullah Al Miraj et al.	48	cites it
2021-02-25	Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks	Neural Computing and Applications	Kapal Dev, Sunder Ali Khowaja, Ankur Singh Bist et al.	37	cites it
2021-08-26	GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays	Pattern Recognition	Angelica I. Avilés-Rivero, Philip Sellars, Carola‐Bibiane Schönlieb et al.	36	cites it
2023-03-20	Review on chest pathogies detection systems using deep learning techniques	Artificial Intelligence Review	Arshia Rehman, Ahmad Khan, Gohar Fatima et al.	25	cites it
2026-02-01	Automatic semantic segmentation in chest X-ray images using deep learning approaches: a literature review	Neural Computing and Applications	Omar Abueed, Priyank Thakkar, Wafa’ H. AlAlaween et al.	2	cites it
2026-09-01	AI-driven techniques for thoracic disease classification in chest radiography: A comprehensive review and critical analysis	Neural Computing and Applications	Yosra Didi, Ahlem Walha, Ali Wali	0	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). rsna-pneumonia-detection-challenge: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-rsna-pneumonia-detection-challenge

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

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