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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine-learning-based high-benefit approach versus conventional high-risk approach in blood pressure management
Kosuke Inoue, Susan Athey, Yusuke Tsugawa
International Journal of Epidemiology (2023) Vol. 52, Iss. 4, pp. 1243-1256
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice
Rohan Khera, Evangelos K. Oikonomou, Girish N. Nadkarni, et al.
Journal of the American College of Cardiology (2024) Vol. 84, Iss. 1, pp. 97-114
Closed Access | Times Cited: 51
Machine learning who to nudge: Causal vs predictive targeting in a field experiment on student financial aid renewal
Susan Athey, Niall Keleher, Jann Spiess
Journal of Econometrics (2025), pp. 105945-105945
Closed Access | Times Cited: 2
Heterogeneous effects of Medicaid coverage on cardiovascular risk factors: secondary analysis of randomized controlled trial
Kosuke Inoue, Susan Athey, Katherine Baicker, et al.
BMJ (2024), pp. e079377-e079377
Closed Access | Times Cited: 8
Harnessing causal forests for epidemiologic research: key considerations
Koichiro Shiba, Kosuke Inoue
American Journal of Epidemiology (2024) Vol. 193, Iss. 6, pp. 813-818
Closed Access | Times Cited: 4
What Epidemiologists Can Do in the Era of Machine Learning and Artificial Intelligence
Akihiro Nishi, Kosuke Inoue
Journal of Epidemiology (2025)
Open Access
Generalized framework for identifying meaningful heterogenous treatment effects in observational studies: A parametric data-adaptive G-computation approach
Roch A. Nianogo, Stephen O’Neill, Kosuke Inoue
Statistical Methods in Medical Research (2025)
Closed Access
Two-step pragmatic subgroup discovery for heterogeneous treatment effects analyses: perspectives toward enhanced interpretability
Toshiaki Komura, Falco J. Bargagli-Stoffi, Koichiro Shiba, et al.
European Journal of Epidemiology (2025)
Open Access
Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management
Antonis A. Armoundas, Faraz S. Ahmad, Zachi I. Attia, et al.
Hypertension (2025)
Closed Access
Artificial intelligence to improve cardiovascular population health
Benjamin Meder, Folkert W. Asselbergs, Euan A. Ashley
European Heart Journal (2025)
Open Access
Reformulating patient stratification for targeting interventions by accounting for severity of downstream outcomes resulting from disease onset: a case study in sepsis
Fahad Kamran, Donna Tjandra, Thomas S. Valley, et al.
Journal of the American Medical Informatics Association (2025)
Closed Access
Poverty and Childhood Obesity: Current Evidence and Methodologies for Future Research
Richard Liang, Ryunosuke Goto, Yusuke Okubo, et al.
Current Obesity Reports (2025) Vol. 14, Iss. 1
Open Access
When, why and how are estimated effects transported between populations? A scoping review of studies applying transportability methods
Fabian Manke-Reimers, Vincent Brugger, Till Bärnighausen, et al.
European Journal of Epidemiology (2025)
Open Access
Heterogeneity of Survival Benefit Conferred by Letermovir
Yu Akahoshi, Hideki Nakasone, Katsuto Takenaka, et al.
Transplantation and Cellular Therapy (2025)
Closed Access
Effectiveness of antibiotic prophylaxis for acute esophageal variceal bleeding in patients with band ligation: A large observational study
Chikamasa Ichita, Sayuri Shimizu, Tadahiro Goto, et al.
World Journal of Gastroenterology (2024) Vol. 30, Iss. 3, pp. 238-251
Open Access | Times Cited: 3
Machine learning for detection of heterogeneous effects of Medicaid coverage on depression
Ryunosuke Goto, Kosuke Inoue, Itsuki Osawa, et al.
American Journal of Epidemiology (2024) Vol. 193, Iss. 7, pp. 951-958
Open Access | Times Cited: 3
Heterogeneous Association of Tooth Loss with Functional Limitations
Yusuke Matsuyama, Jun Aida, Katsunori Kondo, et al.
Journal of Dental Research (2024) Vol. 103, Iss. 4, pp. 369-377
Closed Access | Times Cited: 2
Machine learning reveals heterogeneous associations between environmental factors and cardiometabolic diseases across polygenic risk scores
Tatsuhiko Naito, Kosuke Inoue, Shinichi Namba, et al.
Communications Medicine (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 2
A state-of-the-art review of functional magnetic resonance imaging technique integrated with advanced statistical modeling and machine learning for primary headache diagnosis
Ming-Lin Li, Fei Zhang, Yi‐Yang Chen, et al.
Frontiers in Human Neuroscience (2023) Vol. 17
Open Access | Times Cited: 6
Impact of the PATH Statement on Analysis and Reporting of Heterogeneity of Treatment Effect in Clinical Trials: A Scoping Review
Joe V. Selby, Carolien C H M Maas, Bruce Fireman, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Does clinical practice supported by artificial intelligence improve hypertension care management? A pilot systematic review
Toshiki Maeda, Yuki Sakamoto, Satoshi Hosoki, et al.
Hypertension Research (2024) Vol. 47, Iss. 9, pp. 2312-2316
Closed Access | Times Cited: 1
Causal inference and machine learning in endocrine epidemiology
Kosuke Inoue
Endocrine Journal (2024) Vol. 71, Iss. 10, pp. 945-953
Open Access | Times Cited: 1
Comparison of antimicrobial therapy termination in febrile and afebrile patients with acute cholangitis after drainage
Sakue Masuda, Yoshinori Imamura, Chikamasa Ichita, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Transportability Analysis—A Tool for Extending Trial Results to a Representative Target Population
Kosuke Inoue, William Hsu
JAMA Network Open (2024) Vol. 7, Iss. 1, pp. e2346302-e2346302
Open Access
Updates in the management of hypertension
Sara Ramdani, I. Haddiya
Annals of Medicine and Surgery (2024)
Open Access
Identifying the high-benefit population for weight management-based cardiovascular disease prevention in Japan
Sho Tano, Tomomi Kotani, Seiko Matsuo, et al.
Preventive Medicine Reports (2024) Vol. 43, pp. 102782-102782
Open Access
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