---
title: "Chest X-ray (CheXpert, ChestX-ray14): papers using it"
description: "From Nov 2023 to Oct 2026, 84 archived papers mentioned Chest X-ray (CheXpert, ChestX-ray14) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Sep 2026 (6)."
url: https://scholar4ai.com/datasets/chest-x-ray-chexpert-chestx-ray14
markdown_url: https://scholar4ai.com/datasets/chest-x-ray-chexpert-chestx-ray14.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 84 archived papers mentioned Chest X-ray (CheXpert, ChestX-ray14) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Sep 2026… (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# Chest X-ray (CheXpert, ChestX-ray14)

[Browse dataset profiles](https://scholar4ai.com/datasets/directory.md)

Clinical records, medical images and physiological signals used in medical machine learning.

- data category: Medical and clinical datasets
- 0 papers in the last 7 days
- Names searched for: CheXpert, ChestX-ray14, ChestX-ray8, NIH Chest X-ray

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Medical and clinical datasets datasets: https://scholar4ai.com/datasets/medical-and-clinical-datasets.md



## Key findings

- From Nov 2023 to Oct 2026, 84 archived papers mentioned Chest X-ray (CheXpert, ChestX-ray14) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Sep 2026 (6).
- Chest X-ray (CheXpert, ChestX-ray14) was mentioned in 2 papers in the last 30 days (2026-10-07 to 2026-11-05), ranking #127 of the 246 datasets mentioned.
- By journal category: AI (2).
- Most of them appeared in Artificial Intelligence Review (2).
- From 2017 to 2026 (so far), Chest X-ray (CheXpert, ChestX-ray14) was mentioned in 96 papers in the tracked journals, most of them in AI (93), statistics (1) and information systems (1).
- 28 of them were published in 2025, against 0 in 2017.
- Since 2023, the institutions with the most of these papers were Hong Kong University of Science and Technology (4), Shanghai Artificial Intelligence Laboratory (4) and Carnegie Mellon University (3).
- The journals publishing most of them were Artificial Intelligence Review (13), IEEE Transactions on Pattern Analysis and Machine Intelligence (12) and Pattern Recognition (9).
- The most-cited of them is “Federated learning for medical image analysis: A survey” (Pattern Recognition, 2024), with 522 citations.
- Papers use Chest X-ray (CheXpert, ChestX-ray14) most often with ImageNet (35), MIMIC (29) and Kaggle (17); it has 24 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 21 | 34 | 29 | 84 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 1 | 1 | 2 | 0 | 5 | 7 | 24 | 27 | 26 |
| [Statistics](https://scholar4ai.com/categories/statistics.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| All categories | 0 | 1 | 1 | 2 | 0 | 5 | 7 | 24 | 28 | 28 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 13 |
| 2 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 12 |
| 3 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 9 |
| 4 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 8 |
| 5 | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 7 |
| 6 | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 5 |
| 7 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 4 |
| 8 | [Artificial Intelligence in Medicine](https://scholar4ai.com/journals/artificial-intelligence-in-medicine.md) | 3 |
| 9 | [Medical Image Analysis](https://scholar4ai.com/journals/medical-image-analysis.md) | 3 |
| 10 | [IEEE Transactions on Artificial Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-artificial-intelligence.md) | 3 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Hong Kong University of Science and Technology](https://scholar4ai.com/institutions/hong-kong-university-of-science-and-technology.md) | 4 |
| 2 | Shanghai Artificial Intelligence Laboratory | 4 |
| 3 | [Carnegie Mellon University](https://scholar4ai.com/institutions/carnegie-mellon-university.md) | 3 |
| 4 | [Hong Kong Polytechnic University](https://scholar4ai.com/institutions/hong-kong-polytechnic-university.md) | 3 |
| 5 | [National University of Singapore](https://scholar4ai.com/institutions/national-university-of-singapore.md) | 3 |
| 6 | [Northwestern Polytechnical University](https://scholar4ai.com/institutions/northwestern-polytechnical-university.md) | 3 |
| 7 | ShanghaiTech University | 3 |
| 8 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 3 |
| 9 | Ain Shams University | 2 |
| 10 | Brown University | 2 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 31 |
| 2 | United States | 25 |
| 3 | Australia | 12 |
| 4 | United Kingdom | 12 |
| 5 | Hong Kong | 10 |
| 6 | India | 9 |
| 7 | Germany | 6 |
| 8 | South Korea | 5 |
| 9 | Singapore | 5 |
| 10 | Egypt | 4 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | CheXpert | 10 |
| 2 | medical image analysis | 10 |
| 3 | medical image classification | 10 |
| 4 | chest radiography | 9 |
| 5 | [explainable AI](https://scholar4ai.com/keywords/explainable-ai.md) | 8 |
| 6 | clinical decision support | 7 |
| 7 | [interpretability](https://scholar4ai.com/keywords/interpretability.md) | 7 |
| 8 | MIMIC-CXR | 6 |
| 9 | chest X-ray classification | 6 |
| 10 | [convolutional neural networks](https://scholar4ai.com/keywords/convolutional-neural-networks.md) | 6 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 522 | 16.4 | [Federated learning for medical image analysis: A survey](https://doi.org/10.1016/j.patcog.2024.110424) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2024-03-12 | Hao Guan, Pew‐Thian Yap, Andrea Bozoki et al. |
| 2 | 395 | 11.9 | [Vertical Federated Learning: Concepts, Advances, and Challenges](https://doi.org/10.1109/tkde.2024.3352628) | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | 2024-01-26 | Yang Liu, Yan Kang, Tianyuan Zou et al. |
| 3 | 341 | 13.0 | [Frequency-Aware Feature Fusion for Dense Image Prediction](https://doi.org/10.1109/tpami.2024.3449959) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2024-08-26 | Linwei Chen, Ying Fu, Lin Gu et al. |
| 4 | 186 | 7.8 | [Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications](https://doi.org/10.1007/s10462-024-11005-9) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-11-07 | Haseeb Javed, Shaker El–Sappagh, Tamer Abuhmed |
| 5 | 180 | 5.3 | [The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review](https://doi.org/10.1007/s00521-023-09366-3) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2024-01-13 | Zahra Amiri, Arash Heidari, Nima Jafari Navimipour et al. |

## Used together with

Papers use Chest X-ray (CheXpert, ChestX-ray14) most often with ImageNet (35), MIMIC (29) and Kaggle (17); it has 24 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

*What papers use Chest X-ray (CheXpert, ChestX-ray14) together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [ImageNet](https://scholar4ai.com/datasets/imagenet.md) | Dataset | 35 | 7.4 |
| [MIMIC](https://scholar4ai.com/datasets/mimic.md) | Dataset | 29 | 42.8 |
| [Kaggle](https://scholar4ai.com/datasets/kaggle.md) | Dataset | 17 | 14.7 |
| [CIFAR-10 / CIFAR-100](https://scholar4ai.com/datasets/cifar-10-cifar-100.md) | Dataset | 14 | 5.0 |
| [MNIST / Fashion-MNIST](https://scholar4ai.com/datasets/mnist-fashion-mnist.md) | Dataset | 12 | 5.4 |
| [BraTS](https://scholar4ai.com/datasets/brats.md) | Dataset | 10 | 18.3 |
| [ADNI](https://scholar4ai.com/datasets/adni.md) | Dataset | 8 | 16.3 |
| [Hugging Face Hub](https://scholar4ai.com/datasets/hugging-face-hub.md) | Dataset | 7 | 7.5 |
| [Wikipedia](https://scholar4ai.com/datasets/wikipedia.md) | Dataset | 7 | 3.4 |
| [Fine-grained benchmarks (CUB-200, Stanford Cars, Oxford Flowers)](https://scholar4ai.com/datasets/fine-grained-benchmarks-cub-200-stanford-cars-oxford-flowers.md) | Dataset | 6 | 13.1 |
| [MS COCO](https://scholar4ai.com/datasets/ms-coco.md) | Dataset | 6 | 3.2 |
| [ISIC skin lesion archive](https://scholar4ai.com/datasets/isic-skin-lesion-archive.md) | Dataset | 5 | 25.7 |

The whole network: https://scholar4ai.com/code/network.md

## Papers

*Papers mentioning Chest X-ray (CheXpert, ChestX-ray14) in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-23 | [Retrieval-augmented generation in biomedicine: a survey of technologies, datasets, and clinical applications](https://doi.org/10.1007/s10462-026-11743-y) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Jiawei He, Boya Zhang, Hossein Rouhizadeh et al. | University of Geneva; Hunan City University; Henan University; … |
| 2026-10-20 | [Adaptation of foundation models in medical image analysis: mechanisms, evidence, and deployment considerations](https://doi.org/10.1007/s10462-026-11733-0) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Karma Phuntsho, Abdullah, Kyungmi Lee et al. | James Cook University |

## Cite this page

Scholar4AI. (2026). Chest X-ray (CheXpert, ChestX-ray14). Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/chest-x-ray-chexpert-chestx-ray14

```bibtex
@misc{scholar4ai-datasets-chest-x-ray-chexpert-chestx-ray14,
  author = {{Scholar4AI}},
  title = {Chest X-ray (CheXpert, ChestX-ray14)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/chest-x-ray-chexpert-chestx-ray14}},
  urldate = {2026-11-05},
  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/).