---
title: "National Institutes of Health: funded research papers"
description: "From 2017 to 2026 (so far), National Institutes of Health was named as a funder of 1,566 papers in the tracked journals, most of them in AI (529), statistics (348) and health economics and policy (259). It ranks #46 among the funders of the tracked journals' papers from 2023 to 2025."
url: https://scholar4ai.com/funders/national-institutes-of-health
markdown_url: https://scholar4ai.com/funders/national-institutes-of-health.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From 2017 to 2026 (so far), National Institutes of Health was named as a funder of 1,566 papers in the tracked journals, most of them in AI (529), statistics (348) and health economics and policy (259). (as of 2026-10-31)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-31T17:45:59+09:00
window: 2026-10-02 to 2026-10-31
source: OpenAlex (CC0)
---

# National Institutes of Health

Papers in the tracked journals that name National Institutes of Health as a funder. Funders are the organisations OpenAlex links to a paper from its funding information (Crossref metadata and the paper's acknowledgements); a paper counts once for each funder it names. Grant numbers are not shown.

Back to the ranking: https://scholar4ai.com/rankings/funders.md

## Key findings

- From 2017 to 2026 (so far), National Institutes of Health was named as a funder of 1,566 papers in the tracked journals, most of them in AI (529), statistics (348) and health economics and policy (259).
- It ranks #46 among the funders of the tracked journals' papers from 2023 to 2025.
- 167 of them were published in 2025, against 140 in 2017.
- Since 2023, the institutions with the most of these papers were Harvard University (50), University of Pennsylvania (33) and Stanford University (25).
- The journals publishing most of them were Nature Machine Intelligence (57), Pattern Recognition (36) and Computational Statistics & Data Analysis (32).
- The most-cited of them is “Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead” (Nature Machine Intelligence, 2019), with 10,516 citations.

## 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) | 25 | 24 | 27 | 48 | 68 | 81 | 69 | 68 | 74 | 45 |
| [Statistics](https://scholar4ai.com/categories/statistics.md) | 41 | 45 | 41 | 21 | 31 | 45 | 31 | 33 | 31 | 29 |
| [Health Economics and Policy](https://scholar4ai.com/categories/health-economics-and-policy.md) | 28 | 30 | 30 | 27 | 26 | 25 | 23 | 34 | 23 | 13 |
| [Economics](https://scholar4ai.com/categories/economics.md) | 29 | 28 | 32 | 24 | 36 | 25 | 24 | 27 | 16 | 16 |
| [Higher Education and Research](https://scholar4ai.com/categories/higher-education-and-research.md) | 8 | 7 | 8 | 6 | 5 | 4 | 3 | 6 | 7 | 4 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 7 | 5 | 4 | 5 | 10 | 6 | 1 | 7 | 8 | 3 |
| [Management](https://scholar4ai.com/categories/management.md) | 0 | 5 | 4 | 5 | 3 | 5 | 0 | 1 | 4 | 1 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 1 | 2 | 1 | 3 | 3 | 2 | 0 | 2 | 2 | 0 |
| [Finance](https://scholar4ai.com/categories/finance.md) | 1 | 2 | 1 | 1 | 0 | 2 | 1 | 0 | 2 | 0 |
| [Tourism and Hospitality](https://scholar4ai.com/categories/tourism-and-hospitality.md) | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 |
| [Marketing](https://scholar4ai.com/categories/marketing.md) | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
| All categories | 140 | 149 | 149 | 142 | 182 | 195 | 153 | 178 | 167 | 111 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 57 |
| 2 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 36 |
| 3 | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 32 |
| 4 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 24 |
| 5 | [Journal of Health Economics](https://scholar4ai.com/journals/journal-of-health-economics.md) | 22 |
| 6 | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 22 |
| 7 | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 21 |
| 8 | [Journal of Multivariate Analysis](https://scholar4ai.com/journals/journal-of-multivariate-analysis.md) | 17 |
| 9 | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 17 |
| 10 | [Lifetime Data Analysis](https://scholar4ai.com/journals/lifetime-data-analysis.md) | 17 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | Harvard University | 50 |
| 2 | University of Pennsylvania | 33 |
| 3 | Stanford University | 25 |
| 4 | University of North Carolina at Chapel Hill | 25 |
| 5 | Yale University | 23 |
| 6 | Massachusetts Institute of Technology | 20 |
| 7 | University of California, Los Angeles | 19 |
| 8 | Columbia University | 18 |
| 9 | Stanford Medicine | 18 |
| 10 | National Bureau of Economic Research | 17 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 547 |
| 2 | China | 88 |
| 3 | United Kingdom | 39 |
| 4 | Germany | 24 |
| 5 | Canada | 20 |
| 6 | South Korea | 20 |
| 7 | Italy | 16 |
| 8 | Spain | 14 |
| 9 | Netherlands | 14 |
| 10 | Switzerland | 12 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | older adults | 14 |
| 2 | feature selection | 13 |
| 3 | [contrastive learning](https://scholar4ai.com/keywords/contrastive-learning.md) | 12 |
| 4 | gender differences | 12 |
| 5 | Alzheimer's disease | 11 |
| 6 | deep learning | 11 |
| 7 | high-dimensional data | 11 |
| 8 | [COVID-19 pandemic](https://scholar4ai.com/keywords/covid-19-pandemic.md) | 10 |
| 9 | educational attainment | 10 |
| 10 | data augmentation | 9 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 10,516 | 117.3 | [Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead](https://doi.org/10.1038/s42256-019-0048-x) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2019-05-13 | Cynthia D Rudin |
| 2 | 10,493 | 128.8 | [From local explanations to global understanding with explainable AI for trees](https://doi.org/10.1038/s42256-019-0138-9) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2020-01-17 | Scott Lundberg, Gabriel Erion, Hugh Chen et al. |
| 3 | 1,561 | 17.5 | [A comparison of random forest variable selection methods for classification prediction modeling](https://doi.org/10.1016/j.eswa.2019.05.028) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2019-05-23 | Jaime Lynn Speiser, Michael E. Miller, Janet Austin Tooze et al. |
| 4 | 1,026 | 9.8 | [Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression](https://doi.org/10.1016/j.ijinfomgt.2018.01.012) | [International Journal of Information Management](https://scholar4ai.com/journals/international-journal-of-information-management.md) | 2018-02-22 | Amandeep Dhir, Yossiri Yossatorn, Puneet Kaur et al. |
| 5 | 781 | 26.2 | [Augmenting large language models with chemistry tools](https://doi.org/10.1038/s42256-024-00832-8) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2024-05-08 | Andres M Bran, Sam Cox, Oliver Tobias Schilter et al. |
| 6 | 743 | 7.7 | [Generalized Latent Multi-View Subspace Clustering](https://doi.org/10.1109/tpami.2018.2877660) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2018-10-24 | Changqing Zhang, Huazhu Fu, Qinghua Hu et al. |
| 7 | 665 | 14.2 | [Three types of incremental learning](https://doi.org/10.1038/s42256-022-00568-3) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2022-12-05 | Gido M. van de Ven, Tinne Tuytelaars, Andreas Savas Tolias |
| 8 | 631 | 9.7 | [AI for radiographic COVID-19 detection selects shortcuts over signal](https://doi.org/10.1038/s42256-021-00338-7) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 2021-05-31 | Alex J. DeGrave, Joseph D. Janizek, Su‐In Lee |
| 9 | 603 | 7.8 | [Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China](https://doi.org/10.1007/s00148-020-00778-2) | [Journal of Population Economics](https://scholar4ai.com/journals/journal-of-population-economics.md) | 2020-05-09 | Yun Qiu, Xi Chen, Wei Kang Shi |
| 10 | 544 | 5.8 | [Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI](https://doi.org/10.1109/tpami.2018.2889096) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2018-12-21 | Chunfeng Lian, Mingxia Liu, Jun Zhang et al. |

## Cite this page

Scholar4AI. (2026). National Institutes of Health. Journal Research Rankings. Retrieved October 31, 2026, from https://scholar4ai.com/funders/national-institutes-of-health

```bibtex
@misc{scholar4ai-funders-national-institutes-of-health,
  author = {{Scholar4AI}},
  title = {National Institutes of Health},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/funders/national-institutes-of-health}},
  urldate = {2026-10-31},
  note = {Journal 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/).