ReviewCurrent hypertension reports2018
Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.
Review in Current hypertension reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses 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
36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 92 citations in OpenAlex.
- Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.Hypertension (Dallas, Tex. : 1979) · 2026Pooled it
- Machine learning prediction in cardiovascular diseases: a meta-analysis.Scientific reports · 2020Pooled it
- Artificial intelligence model comparison for risk factor analysis of patent ductus arteriosus in nationwide very low birth weight infants cohort.Scientific reports · 2021Trial
- Artificial intelligence in periodontal disease research: a bibliometric and visualized analysis of global research trends (2007-2025).The Saudi dental journal · 2026Review
- The Japanese Society of Hypertension Guidelines for blood pressure control using digital technologies.Hypertension research : official journal of the Japanese Society of Hypertension · 2026Article
- A comprehensive narrative review on precision medicine approach to hypertension: exploring the role of genetics, epigenetics, microbiome, and artificial intelligence.Journal of health, population, and nutrition · 2025Review
- Assessing the Efficacy of Various Machine Learning Algorithms in Predicting Blood Pressure Using Pulse Transit Time.Diagnostics (Basel, Switzerland) · 2025Article
- Predicting the effectiveness of drugs used for treating cardiovascular conditions in newborn infants.Pediatric research · 2024Article
- Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review.Cureus · 2024Review
- Digital hypertension towards to the anticipation medicine.Hypertension research : official journal of the Japanese Society of Hypertension · 2023Review
- Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives.Sensors (Basel, Switzerland) · 2023Review
- Work unit level personnel working hours and the patients' length of in-hospital stay-An administrative data approach.PLOS digital health · 2023Article
- Deep Learning for Echocardiography: Introduction for Clinicians and Future Vision: State-of-the-Art Review.Life (Basel, Switzerland) · 2023Review
- Artificial Intelligence in Hypertension Management: An Ace up Your Sleeve.Journal of cardiovascular development and disease · 2023Review
- RETRACTED ARTICLE: Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda.Journal of ambient intelligence and humanized computing · 2023Article
- Dynamic prediction of life-threatening events for patients in intensive care unit.BMC medical informatics and decision making · 2022Article
- Development of artificial neural networks for early prediction of intestinal perforation in preterm infants.Scientific reports · 2022Article
- Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.Biosensors · 2022Article
- Artificial Intelligence and Cardiovascular Genetics.Life (Basel, Switzerland) · 2022Review
- Classification of Electrocardiography Hybrid Convolutional Neural Network-Long Short Term Memory with Fully Connected Layer.Computational intelligence and neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewEvidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and future implications of AI in hypertension management and clinical trials, with an eye towards personalized medicine. RECENT
findingsAlthough recent studies demonstrate that AI in hypertension research is feasible and possibly useful, AI-informed care has yet to transform blood pressure (BP) control. This is due, in part, to lack of data on AI's consistency, accuracy, and reliability in the BP sphere. However, many factors contribute to poorly controlled BP, including biological, environmental, and lifestyle issues. AI allows insight into extrapolating data analytics to inform prescribers and patients about specific factors that may impact their BP control. To date, AI has been mainly used to investigate risk factors for hypertension, but has not yet been utilized for hypertension management due to the limitations of study design and of physician's engagement in computer science literature. The future of AI with more robust architecture using multi-omics approaches and wearable technology will likely be an important tool allowing to incorporate biological, lifestyle, and environmental factors into decision-making of appropriate drug use for BP control.
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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.