---
title: "tawsifurrahman/covid19-radiography-database"
description: "23 papers in the tracked journals link to the Kaggle dataset tawsifurrahman/covid19-radiography-database in their Crossref records, the first in 2021; most of them (9) in 2021."
url: https://scholar4ai.com/code/kaggle-tawsifurrahman-covid19-radiography-database
markdown_url: https://scholar4ai.com/code/kaggle-tawsifurrahman-covid19-radiography-database.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "23 papers in the tracked journals link to the Kaggle dataset tawsifurrahman/covid19-radiography-database in their Crossref records, the first in 2021; most of them (9) 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)
---

# tawsifurrahman/covid19-radiography-database: papers linking to it

Research papers in the 480 tracked journals that link to tawsifurrahman/covid19-radiography-database (https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database), 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/tawsifurrahman/covid19-radiography-database

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

## Key findings

- 23 papers in the tracked journals link to the Kaggle dataset tawsifurrahman/covid19-radiography-database in their Crossref records, the first in 2021; most of them (9) in 2021.
- By category: AI (22) and Information Systems (1); the journals with the most are Neural Computing and Applications (12), Cognitive Computation (3) and Expert Systems with Applications (3).
- 2 of the papers build on one another: a later paper cites an earlier one that also links tawsifurrahman/covid19-radiography-database.

## By year

*Papers linking to tawsifurrahman/covid19-radiography-database by publication year*

| Year | Papers |
|---|---:|
| 2021 | 9 |
| 2022 | 3 |
| 2023 | 4 |
| 2024 | 3 |
| 2025 | 2 |
| 2026 | 2 |

## Journals

*Journals whose papers link to tawsifurrahman/covid19-radiography-database most*

| Journal | Papers |
|---|---:|
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 12 |
| [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 3 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 3 |
| [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 1 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Lightweight ResGRU: a deep learning-based prediction of SARS-CoV-2 (COVID-19) and its severity classification using multimodal chest radiography images](https://doi.org/10.1007/s00521-023-08200-0) (Neural Computing and Applications, 2023)
  - [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, 2025) — cites the paper above

## Papers

*Papers linking to tawsifurrahman/covid19-radiography-database, 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 |
| 2024-06-12 | [Iterative enhancement fusion-based cascaded model for detection and localization of multiple disease from CXR-Images](https://doi.org/10.1016/j.eswa.2024.124464) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Satvik Vats, Vikrant Sharma, Karan Singh et al. | 392 | cites it |
| 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 |
| 2021-01-19 | [Efficient deep learning approach for augmented detection of Coronavirus disease](https://doi.org/10.1007/s00521-020-05410-8) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Ahmed Sedik, Mohamed Adel Hammad, Fathi E. Abd El‐Samie et al. | 188 | 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 | [COV19-CNNet and COV19-ResNet: Diagnostic Inference Engines for Early Detection of COVID-19](https://doi.org/10.1007/s12559-020-09795-5) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Aytürk Keleş, Mustafa Berk Keles, Mustafa Berk Keles et al. | 73 | cites it |
| 2023-03-17 | [Lightweight deep CNN-based models for early detection of COVID-19 patients from chest X-ray images](https://doi.org/10.1016/j.eswa.2023.119900) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Haval Ismael Hussein, Abdulhakeem O. Mohammed, Masoud Muhammed Hassan et al. | 70 | 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](https://doi.org/10.1007/s12559-022-10076-6) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 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](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 |
| 2021-02-25 | [Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks](https://doi.org/10.1007/s00521-020-05641-9) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Kapal Dev, Sunder Ali Khowaja, Ankur Singh Bist et al. | 37 | 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 |
| 2023-02-20 | [Evaluation of EfficientNet models for COVID-19 detection using lung parenchyma](https://doi.org/10.1007/s00521-023-08344-z) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Zühal Kurt, Şahin Işık, Zeynep Kaya et al. | 31 | cites it |
| 2022-01-08 | [Classification of Covid-19 chest X-ray images by means of an interpretable evolutionary rule-based approach](https://doi.org/10.1007/s00521-021-06806-w) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Ivanoe De Falco, Giuseppe De Pietro, Giovanna Sannino | 26 | cites it |
| 2023-01-24 | [Lightweight ResGRU: a deep learning-based prediction of SARS-CoV-2 (COVID-19) and its severity classification using multimodal chest radiography images](https://doi.org/10.1007/s00521-023-08200-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Mughees Ahmad, Usama Ijaz Bajwa, Yasar Mehmood et al. | 20 | cites it |
| 2024-02-19 | [Adapting transfer learning models to dataset through pruning and Avg-TopK pooling](https://doi.org/10.1007/s00521-024-09484-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Cüneyt Özdemir | 19 | 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 |
| 2023-07-24 | [Online diagnosis of COVID-19 from chest radiography images by using deep learning algorithms](https://doi.org/10.1007/s00521-023-08867-5) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Cafer Budak, Vasfiye Mençik, Osman Varışlı | 5 | cites it |
| 2024-01-23 | [A novel hybridization approach to improve the critical distance clustering algorithm: Balancing speed and quality](https://doi.org/10.1016/j.eswa.2024.123298) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Farag Hamed Kuwil, Ümit Atila | 2 | 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 |
| 2025-10-31 | [A different perspective on the diagnosis of COVID-19 disease with the developed quadstar local binary pattern method](https://doi.org/10.1007/s00521-025-11640-5) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Mehmet Gül | 0 | cites it |
| 2026-01-29 | [An interactive axial feature selection network for medical image classification](https://doi.org/10.1016/j.neunet.2026.108661) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Shuai Pang, Chunhua Hu, Juan Zhao et al. | 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). tawsifurrahman/covid19-radiography-database: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-tawsifurrahman-covid19-radiography-database

```bibtex
@misc{scholar4ai-code-kaggle-tawsifurrahman-covid19-radiography-database,
  author = {{Scholar4AI}},
  title = {tawsifurrahman/covid19-radiography-database: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-tawsifurrahman-covid19-radiography-database}},
  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/).