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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:

Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve
Valeria Visco, Carmine Izzo, Costantino Mancusi, et al.
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 2, pp. 74-74
Open Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Navigating the doctor-patient-AI relationship - a mixed-methods study of physician attitudes toward artificial intelligence in primary care
Matthew R. Allen, Sophie Webb, Ammar Mandvi, et al.
BMC Primary Care (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 17
Artificial Intelligence Technologies in Cardiology
Łukasz Ledziński, Grzegorz Grześk
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 5, pp. 202-202
Open Access | Times Cited: 27
Revolutionizing Cardiology through Artificial Intelligence—Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment—A Comprehensive Review of the Past 5 Years
Elena Stamate, Alin Ionut Piraianu, Oana Roxana Ciobotaru, et al.
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1103-1103
Open Access | Times Cited: 7
Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia
Md. Merajul Islam, Md. Jahangir Alam, Md. Maniruzzaman, et al.
PLoS ONE (2023) Vol. 18, Iss. 8, pp. e0289613-e0289613
Open Access | Times Cited: 21
Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study
Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, et al.
Clinical and Experimental Hypertension (2025) Vol. 47, Iss. 1
Open Access
Development and Internal Validation of an AI-Enabled Cuff-less, Non-invasive Continuous Blood Pressure Monitor Across All Classes of Hypertension
Francisco López-Jiménez, Abhishek Deshmukh, John D. Bisognano, et al.
Journal of Cardiovascular Translational Research (2025)
Open Access
Artificial Intelligence and Machine Learning for Medical Applications and Digital Health
Valeria Visco, Carmine Vecchione, Gianni D’Angelo, et al.
(2025), pp. 1-15
Closed Access
Assessing the Efficacy of Various Machine Learning Algorithms in Predicting Blood Pressure Using Pulse Transit Time
Ahmad F. Turki
Diagnostics (2025) Vol. 15, Iss. 3, pp. 261-261
Open Access
Advancing personalized medicine in digital health: The role of artificial intelligence in enhancing clinical interpretation of 24-h ambulatory blood pressure monitoring
Sreyoshi F. Alam, Charat Thongprayoon, Jing Miao, et al.
Digital Health (2025) Vol. 11
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
Polypill Therapy for Cardiovascular Disease Prevention and Combination Medication Therapy for Hypertension Management
Keisuke Narita, Satoshi Hoshide, Kazuomi Kario
Journal of Clinical Medicine (2023) Vol. 12, Iss. 23, pp. 7226-7226
Open Access | Times Cited: 7
Transforming Healthcare: The AI Revolution in the Comprehensive Care of Hypertension
Sreyoshi F. Alam, Maria Lourdes Gonzalez Suarez
Clinics and Practice (2024) Vol. 14, Iss. 4, pp. 1357-1374
Open Access | Times Cited: 2
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
Smart solutions in hypertension diagnosis and management: a deep dive into artificial intelligence and modern wearables for blood pressure monitoring
Anubhuti Juyal, Shradha Bisht, Mamta F. Singh
Blood Pressure Monitoring (2024) Vol. 29, Iss. 5, pp. 260-271
Closed Access | Times Cited: 1
Evolving Health Monitoring: Nanoscale Flexible Electronics for Noninvasive Uric Acid Analysis in Sweat
C Ma, Xudong Shang, Ziyu Zhu, et al.
TrAC Trends in Analytical Chemistry (2024) Vol. 179, pp. 117889-117889
Closed Access | Times Cited: 1
Revolutionizing AI-driven Hypertension Care: A Review of Current Trends and Future Directions
Zeib Jahangir, Sara Muddassir Qureshi, Yahya Abdul Rehman, et al.
Journal of Science & Technology (2024) Vol. 5, Iss. 4, pp. 99-132
Open Access | Times Cited: 1
An explainable model for predicting Worsening Heart Failure based on genetic programming
Valeria Visco, Antonio Robustelli, Francesco Loria, et al.
Computers in Biology and Medicine (2024) Vol. 182, pp. 109110-109110
Open Access | Times Cited: 1
Internet of Things and Big Data Analytics in Preventive Healthcare: A Synthetic Review
Urška Šajnovič, Helena Blažun Vošner, Jernej Završnik, et al.
Electronics (2024) Vol. 13, Iss. 18, pp. 3642-3642
Open Access | Times Cited: 1
Artificial intelligence and big data from digital health applications: publication trends and analysis
Selma ARSLANTAŞ
Journal of Health Organization and Management (2024)
Closed Access | Times Cited: 1
Interventions to Address Cardiovascular Risk in Obese Patients: Many Hands Make Light Work
Valeria Visco, Carmine Izzo, Davide Bonadies, et al.
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 8, pp. 327-327
Open Access | Times Cited: 4
A paradigm shift from office to home-based blood pressure measurement approaches in kidney transplant recipients
Ekamol Tantisattamo, Antoney Ferrey, Uttam Reddy, et al.
Current Opinion in Nephrology & Hypertension (2023) Vol. 33, Iss. 1, pp. 67-76
Closed Access | Times Cited: 2
Noncontact remote sensing of abnormal blood pressure using a deep neural network: a novel approach for hypertension screening
Zeye Liu, Hang Li, Wenchao Li, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 12, pp. 8657-8668
Open Access | Times Cited: 2
Inteligencia artificial. Aplicación en las imágenes cardiovasculares y la prevención cardiovascular
Mariano Falconi, Martina Aineseder, Diego Pérez de Arenaza, et al.
Revista Argentina de Cardiología (2024) Vol. 92, Iss. 1, pp. 55-63
Open Access
Vitamin D: A Bridge between Kidney and Heart
Carmine Secondulfo, Valeria Visco, Nicola Virtuoso, et al.
Life (2024) Vol. 14, Iss. 5, pp. 617-617
Open Access
Artificial Intelligence Applications in Health
Ebru Uğraş Tiryaki, Erhan Şimşek
Arşiv Kaynak Tarama Dergisi (2024) Vol. 33, Iss. 2, pp. 98-105
Open Access
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