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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 integration of multimodal data identifies key features of blood pressure regulation
Panayiotis Louca, Tran Tran, Clea du Toit, et al.
EBioMedicine (2022) Vol. 84, pp. 104243-104243
Open Access | Times Cited: 18

Showing 18 citing articles:

Small molecule metabolites: discovery of biomarkers and therapeutic targets
Shi Qiu, Ying Cai, Hong Yao, et al.
Signal Transduction and Targeted Therapy (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 331
Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management
Evan D. Muse, Eric J. Topol
Cell Metabolism (2024) Vol. 36, Iss. 4, pp. 670-683
Closed Access | Times Cited: 12
Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence
Tina Binesh Marvasti, Yuan Gao, Kevin R. Murray, et al.
Canadian Journal of Cardiology (2024) Vol. 40, Iss. 10, pp. 1934-1945
Open Access | Times Cited: 9
Recent developments in machine learning modeling methods for hypertension treatment
Hirohiko Kohjitani, Hiroshi Koshimizu, Kazuki Nakamura, et al.
Hypertension Research (2024) Vol. 47, Iss. 3, pp. 700-707
Closed Access | Times Cited: 8
Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data
Gabin Drouard, Juha Mykkänen, Jarkko S. Heiskanen, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 8
Artificial intelligence to improve cardiovascular population health
Benjamin Meder, Folkert W. Asselbergs, Euan A. Ashley
European Heart Journal (2025)
Open Access
Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms – A systematic review
Xianyu Zhu, Eduard Flores Ventura, Sakshi Bansal, et al.
Computers in Biology and Medicine (2025) Vol. 186, pp. 109661-109661
Open Access
Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer
Wenwen, Zekun Jiang, Jingyan Liu, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
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
Multimodal learning system integrating electronic medical records and hysteroscopic images for reproductive outcome prediction and risk stratification of endometrial injury: a multicenter diagnostic study
Bohan Li, Hui Chen, Xiaona Lin, et al.
International Journal of Surgery (2024)
Open Access | Times Cited: 3
Application of artificial intelligence in hypertension
Jung Sun Cho, Jae‐Hyeong Park
Clinical Hypertension (2024) Vol. 30, Iss. 1
Open Access | Times Cited: 1
Individualized treatment decision model for inoperable elderly esophageal squamous cell carcinoma based on multi-modal data fusion
Yong Huang, Xiaoyu Huang, Anling Wang, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 4
Combating Hypertension Beyond GWAS: Microbiome and Artificial Intelligence as Opportunities for Precision Medicine
Sachin Aryal, Ishan Manandhar, Xue Mei, et al.
Cambridge Prisms Precision Medicine (2023), pp. 1-65
Open Access | Times Cited: 3
Unraveling phenotypic variance in metabolic syndrome through multi-omics
Lamessa Dube Amente, Natalie Mills, Thuc Duy Le, et al.
Human Genetics (2023) Vol. 143, Iss. 1, pp. 35-47
Closed Access | Times Cited: 2
Multimodal data for systolic and diastolic blood pressure prediction: The hypertension conscious artificial intelligence
Quincy A. Hathaway, Naveena Yanamala, Partho P. Sengupta
EBioMedicine (2022) Vol. 84, pp. 104261-104261
Open Access | Times Cited: 3
DeepForest-HTP: A novel deep forest approach for predicting antihypertensive peptides
Qingshun Bai, Hao Chen, Wenshuo Li, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 258, pp. 108514-108514
Open Access
Development of a machine learning-based model for predicting individual responses to antihypertensive treatments
Jiayi Yi, Lili Wang, Jiali Song, et al.
Nutrition Metabolism and Cardiovascular Diseases (2024)
Closed Access
Supervised Learning Algorithm for Predicting Mortality Risk in Older Adults Using Cardiovascular Health Study Dataset
Jean Paul Navarrete, José R. Pinto, Rosa L. Figueroa, et al.
Applied Sciences (2022) Vol. 12, Iss. 22, pp. 11536-11536
Open Access | Times Cited: 2
An Overview of Metabolomics Studies Based on Qatari Population
Fatima Lamya, Afeefa Khalisa, F. Naji, et al.
Studies in health technology and informatics (2023)
Open Access
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