---
title: "paultimothymooney/chest-xray-pneumonia: papers citing it"
description: "24 papers in the tracked journals link to the Kaggle dataset paultimothymooney/chest-xray-pneumonia in their Crossref records, the first in 2020; most of them (7) in 2021."
url: https://scholar4ai.com/code/kaggle-paultimothymooney-chest-xray-pneumonia
markdown_url: https://scholar4ai.com/code/kaggle-paultimothymooney-chest-xray-pneumonia.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "24 papers in the tracked journals link to the Kaggle dataset paultimothymooney/chest-xray-pneumonia in their Crossref records, the first in 2020; most of them (7) 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)
---

# paultimothymooney/chest-xray-pneumonia: papers linking to it

Research papers in the 480 tracked journals that link to paultimothymooney/chest-xray-pneumonia (https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia), 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.

- Kaggle
- https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia

All repositories: https://scholar4ai.com/code.md

## Key findings

- 24 papers in the tracked journals link to the Kaggle dataset paultimothymooney/chest-xray-pneumonia in their Crossref records, the first in 2020; most of them (7) in 2021.
- By category: AI (22) and Information Systems (2); the journals with the most are Neural Computing and Applications (6), Expert Systems with Applications (5) and Applied Intelligence (4).
- 10 of the papers build on one another: a later paper cites an earlier one that also links paultimothymooney/chest-xray-pneumonia.

## By year

*Papers linking to paultimothymooney/chest-xray-pneumonia by publication year*

| Year | Papers |
|---|---:|
| 2020 | 5 |
| 2021 | 7 |
| 2022 | 4 |
| 2023 | 3 |
| 2024 | 1 |
| 2025 | 2 |
| 2026 | 2 |

## Journals

*Journals whose papers link to paultimothymooney/chest-xray-pneumonia most*

| Journal | Papers |
|---|---:|
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 6 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 5 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 4 |
| [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | 2 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices](https://doi.org/10.1007/s10489-020-01826-w) (Applied Intelligence, 2020)
  - [Feature selection of pre-trained shallow CNN using the QLESCA optimizer: COVID-19 detection as a case study](https://doi.org/10.1007/s10489-022-04446-8) (Applied Intelligence, 2023) — cites the paper above
- [Deep learning approaches for COVID-19 detection based on chest X-ray images](https://doi.org/10.1016/j.eswa.2020.114054) (Expert Systems with Applications, 2020)
  - [A preliminary analysis of AI based smartphone application for diagnosis of COVID-19 using chest X-ray images](https://doi.org/10.1016/j.eswa.2021.115401) (Expert Systems with Applications, 2021) — cites the paper above
  - [RESCOVIDTCNnet: A residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images](https://doi.org/10.1016/j.eswa.2022.117410) (Expert Systems with Applications, 2022) — cites the paper above
  - [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, 2022) — cites the paper above
- [CGNet: A graph-knowledge embedded convolutional neural network for detection of pneumonia](https://doi.org/10.1016/j.ipm.2020.102411) (Information Processing & Management, 2020)
  - [Stacked ensemble learning based on deep convolutional neural networks for pediatric pneumonia diagnosis using chest X-ray images](https://doi.org/10.1007/s00521-022-08099-z) (Neural Computing and Applications, 2022) — cites the paper above
- [Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans](https://doi.org/10.1038/s42256-021-00307-0) (Nature Machine Intelligence, 2021)
  - [AI-driven techniques for thoracic disease classification in chest radiography: A comprehensive review and critical analysis](https://doi.org/10.1007/s00521-026-12457-6) (Neural Computing and Applications, 2026) — cites the paper above

## Papers

*Papers linking to paultimothymooney/chest-xray-pneumonia, 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](https://doi.org/10.1038/s42256-021-00307-0) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Michael Roberts, Derek Driggs, Matthew Thorpe et al. | 1,045 | cites it |
| 2020-09-28 | [Deep learning approaches for COVID-19 detection based on chest X-ray images](https://doi.org/10.1016/j.eswa.2020.114054) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Aras Masood Ismael, Abdulkadir Şengür | 748 | cites it |
| 2020-08-20 | [Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices](https://doi.org/10.1007/s10489-020-01826-w) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Sakshi Ahuja, Bijaya Ketan Panigrahi, Nilanjan Dey et al. | 380 | cites it |
| 2020-10-17 | [MetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients](https://doi.org/10.1016/j.patcog.2020.107700) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Mohammad Shorfuzzaman, M. Shamim Hossain | 217 | 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 |
| 2020-10-19 | [CGNet: A graph-knowledge embedded convolutional neural network for detection of pneumonia](https://doi.org/10.1016/j.ipm.2020.102411) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Xiang Yu, Shuihua Wang‎, Yudong Zhang | 109 | cites it |
| 2021-03-04 | [COVID-19 Infection Detection from Chest X-Ray Images Using Hybrid Social Group Optimization and Support Vector Classifier](https://doi.org/10.1007/s12559-021-09848-3) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Asu Kumar Singh, Anupam Kumar, Mufti Mahmud et al. | 96 | cites it |
| 2021-06-09 | [Optimization and fine-tuning of DenseNet model for classification of COVID-19 cases in medical imaging](https://doi.org/10.1016/j.jjimei.2021.100020) | [International Journal of Information Management Data Insights](https://scholar4ai.com/journals/international-journal-of-information-management-data-insights.md) | Tavishee Chauhan, Hemant Palivela, Sarveshmani Tiwari | 95 | cites it |
| 2023-05-27 | [Parallel CNN-ELM: A multiclass classification of chest X-ray images to identify seventeen lung diseases including COVID-19](https://doi.org/10.1016/j.eswa.2023.120528) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Md. Nahiduzzaman, Md. Omaer Faruq Goni, Rakibul Hassan et al. | 74 | cites it |
| 2021-06-12 | [A preliminary analysis of AI based smartphone application for diagnosis of COVID-19 using chest X-ray images](https://doi.org/10.1016/j.eswa.2021.115401) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Aravind Krishnaswamy Rangarajan, Hari Krishnan Ramachandran | 61 | cites it |
| 2022-12-07 | [Stacked ensemble learning based on deep convolutional neural networks for pediatric pneumonia diagnosis using chest X-ray images](https://doi.org/10.1007/s00521-022-08099-z) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | J. Arun Prakash, Vinayakumar Ravi, V. Sowmya et al. | 49 | 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 |
| 2021-01-23 | [A new clustering method for the diagnosis of CoVID19 using medical images](https://doi.org/10.1007/s10489-020-02122-3) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Himanshu Mittal, Avinash Chandra Pandey, Raju Pal et al. | 44 | cites it |
| 2022-04-27 | [RESCOVIDTCNnet: A residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images](https://doi.org/10.1016/j.eswa.2022.117410) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | El‐Sayed A. El‐Dahshan, Mahmoud M. Bassiouni, Ahmed Hagag et al. | 42 | cites it |
| 2021-04-29 | [A novel augmented deep transfer learning for classification of COVID-19 and other thoracic diseases from X-rays](https://doi.org/10.1007/s00521-021-06044-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Fouzia Altaf, Syed Mohammed Shamsul Islam, Naeem Khalid Janjua | 37 | cites it |
| 2024-02-07 | [Self-supervised multi-task learning for medical image analysis](https://doi.org/10.1016/j.patcog.2024.110327) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Huihui Yu, Qun Dai | 34 | cites it |
| 2022-07-21 | [A hybrid random forest deep learning classifier empowered edge cloud architecture for COVID-19 and pneumonia detection](https://doi.org/10.1016/j.eswa.2022.118227) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | M. Hemalatha | 29 | cites it |
| 2023-02-06 | [Feature selection of pre-trained shallow CNN using the QLESCA optimizer: COVID-19 detection as a case study](https://doi.org/10.1007/s10489-022-04446-8) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Qusay Shihab Hamad, Hussein Samma, Shahrel Azmin Suandi | 18 | 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 |
| 2025-04-26 | [Efficient and lightweight CNN model for COVID-19 diagnosis from CT and X-ray images using customized pruning and quantization techniques](https://doi.org/10.1007/s00521-025-11219-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Nattavut Sriwiboon | 14 | cites it |
| 2023-12-08 | [MLDC: multi-lung disease classification using quantum classifier and artificial neural networks](https://doi.org/10.1007/s00521-023-09207-3) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Riya Arora, G. V. Eswara Rao, Shashwati Banerjea et al. | 8 | cites it |
| 2025-12-22 | [UniMedX: A Unified Kolmogorov-Arnold Theory Guided Framework for Interpretable Medical Image Classification and Segmentation](https://doi.org/10.1016/j.knosys.2025.115176) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Ju Zhang, Mingyang Chen, Xuwei Xuan et al. | 1 | cites it |
| 2026-05-01 | [Optimized deep neural network for improved lung disease classification](https://doi.org/10.1007/s00521-026-12078-z) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Mohamed H. Saad, Wessam S. ElAraby, Basem M. ElHalawany et al. | 1 | cites it |
| 2026-09-01 | [AI-driven techniques for thoracic disease classification in chest radiography: A comprehensive review and critical analysis](https://doi.org/10.1007/s00521-026-12457-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 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). paultimothymooney/chest-xray-pneumonia: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-paultimothymooney-chest-xray-pneumonia

```bibtex
@misc{scholar4ai-code-kaggle-paultimothymooney-chest-xray-pneumonia,
  author = {{Scholar4AI}},
  title = {paultimothymooney/chest-xray-pneumonia: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-paultimothymooney-chest-xray-pneumonia}},
  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/).