ReviewJournal of cardiovascular development and disease2023
Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve.
Review in Journal of cardiovascular development and disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- Assessment of ChatGPT-4.0 versus ChatGPT-Mini in Generating Guideline-Based Hypertension Content.Arquivos brasileiros de cardiologia · 2026Article
- Association of Mobile-Enhanced Remote Patient Monitoring with Blood Pressure Control in Hypertensive Patients with Comorbidities: A Multicenter Pre-Post Evaluation.Diagnostics (Basel, Switzerland) · 2026Article
- Review
- A retrospective analysis of influence of the establishment of intelligent hypertension diagnosis and treatment center on blood pressure data management and treatment compliance of patients with hypertension in Sichuan, China, and its clinical value in accurate diagnosis and treatment.BMC cardiovascular disorders · 2025Article
- Prediction of Personalised Hypertension Using Machine Learning in Indonesian Population.Journal of medical systems · 2025Article
- Article
- A Heart-to-Heart With ChatGPT: AI Applications in Hypertension.American journal of hypertension · 2025Review
- Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.Hypertension (Dallas, Tex. : 1979) · 2025Review
- Development and Internal Validation of an AI-Enabled Cuff-less, Non-invasive Continuous Blood Pressure Monitor Across All Classes of Hypertension.Journal of cardiovascular translational research · 2025Article
- Synthetic data as an investigative tool in hypertension and renal diseases research.World journal of methodology · 2025Article
- Assessing the Efficacy of Various Machine Learning Algorithms in Predicting Blood Pressure Using Pulse Transit Time.Diagnostics (Basel, Switzerland) · 2025Article
- Global burden of hypertensive heart disease attributable to high body mass index from 1990 to 2021: a multidimensional analysis and public health response.Frontiers in cardiovascular medicine · 2025Article
- HRP-OG: Online Learning with Generative Feature Replay for Hypertension Risk Prediction in a Nonstationary Environment.Sensors (Basel, Switzerland) · 2024Article
- Transforming Healthcare: The AI Revolution in the Comprehensive Care of Hypertension.Clinics and practice · 2024Review
- 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.Diagnostics (Basel, Switzerland) · 2024Review
- Vitamin D: A Bridge between Kidney and Heart.Life (Basel, Switzerland) · 2024Review
- Navigating the doctor-patient-AI relationship - a mixed-methods study of physician attitudes toward artificial intelligence in primary care.BMC primary care · 2024Article
- Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Noncontact remote sensing of abnormal blood pressure using a deep neural network: a novel approach for hypertension screening.Quantitative imaging in medicine and surgery · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the "black-box" nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients' risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.