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. Also as Markdown.

← Top research funders

Key findings#

From 2017 to 2026 (so far), National Institutes of Health was named as a funder of 1,513 papers in the tracked journals, most of them in AI (529), statistics (348) and economics (251).
It ranks #44 among the funders of the tracked journals' papers from 2023 to 2025.
163 of them were published in 2025, against 132 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#

20172026 (so far)

Papers per publication year and category
Category	2017	2018	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	25	24	27	48	68	81	69	68	74	45
Statistics	41	45	41	21	31	45	31	33	31	29
Economics	29	28	31	23	36	24	23	27	16	14
Health Economics and Policy	21	26	25	20	21	21	21	29	21	13
Operations Research	7	5	4	5	10	6	1	7	8	3
Higher Education and Research	7	7	8	6	4	3	3	6	5	3
Management	0	5	4	5	3	5	0	1	4	1
Information Systems	1	2	1	3	3	2	0	2	2	0
Finance	1	2	1	1	0	2	1	0	2	0
Tourism and Hospitality	0	1	0	1	0	0	1	0	0	0
Marketing	0	0	1	1	0	0	0	0	0	0
All categories	132	145	143	134	176	189	150	173	163	108

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Nature Machine Intelligence	57
2	Pattern Recognition	36
3	Computational Statistics & Data Analysis	32
4	IEEE Transactions on Pattern Analysis and Machine Intelligence	24
5	Journal of Health Economics	22
6	Neural Networks	22
7	Expert Systems with Applications	21
8	Journal of Multivariate Analysis	17
9	Statistics and Computing	17
10	Lifetime Data Analysis	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	22
6	Massachusetts Institute of Technology	20
7	University of California, Los Angeles	19
8	Stanford Medicine	18
9	Columbia University	17
10	University of Michigan	17

Countries with the most papers, since 2023
#	Country	Papers
1	United States	533
2	China	88
3	United Kingdom	36
4	Germany	24
5	Canada	20
6	South Korea	20
7	Italy	15
8	Spain	14
9	Netherlands	14
10	France	11

Keywords with the most papers, since 2023
#	Keyword	Papers
1	older adults	14
2	feature selection	13
3	contrastive learning	12
4	Alzheimer's disease	11
5	deep learning	11
6	gender differences	11
7	high-dimensional data	11
8	COVID-19 pandemic	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	Nature Machine Intelligence	2019-05-13	Cynthia D Rudin
2	10,493	128.8	From local explanations to global understanding with explainable AI for trees	Nature Machine Intelligence	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	Expert Systems with Applications	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	International Journal of Information Management	2018-02-22	Amandeep Dhir, Yossiri Yossatorn, Puneet Kaur et al.
5	781	26.2	Augmenting large language models with chemistry tools	Nature Machine Intelligence	2024-05-08	Andres M Bran, Sam Cox, Oliver Tobias Schilter et al.
6	743	7.7	Generalized Latent Multi-View Subspace Clustering	IEEE Transactions on Pattern Analysis and Machine Intelligence	2018-10-24	Changqing Zhang, Huazhu Fu, Qinghua Hu et al.
7	665	14.2	Three types of incremental learning	Nature Machine Intelligence	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	Nature Machine Intelligence	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	Journal of Population Economics	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	IEEE Transactions on Pattern Analysis and Machine Intelligence	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

@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}
}

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