ArticleScientific reports2018
Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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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.
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Who cites it
27 citing papers in PubMed, 70 citations in OpenAlex.
- Clinical measurements of aortic stiffness and peripheral resistance using a routine echocardiogram.Physiological reports · 2026Article
- [A multi-source information fusion-based method for the local pulse wave velocity estimation in carotid artery].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Smartphone Measurement of Aortic Arch Pulse-Wave Velocity and Total Arterial Compliance: Accessible Local and Global Arterial Stiffness Assessment.Journal of the American Heart Association · 2026Observational
- Arterial Stiffness in Cancer Survivors: The Prognostic Value of Estimated Pulse Wave Velocity in US Cancer Population From the National Health and Nutrition Examination Survey 2009 to 2018.Journal of the American Heart Association · 2025Article
- Assessment of Myocardial Injury Size Metrics Using Carotid Pressure Waveform: Proof-of-Concept in Coronary Occlusion/Reperfusion Rat Model.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population.Scientific reports · 2025Article
- Machine Learning Prediction Model for Carotid-Femoral Pulse Wave Velocity in Cardiovascular Health Assessments.Journal of clinical hypertension (Greenwich, Conn.) · 2025Article
- Neural network-based arterial diameter estimation from ultrasound data.PLOS digital health · 2024Article
- Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing.Health information science and systems · 2024Article
- Adverse Cardiovascular Effects of Nicotine Delivered by Chronic Electronic Cigarettes or Standard Cigarettes Captured by Cardiovascular Intrinsic Frequencies.Journal of the American Heart Association · 2024Article
- Estimation of aortic stiffness by finger photoplethysmography using enhanced pulse wave analysis and machine learning.Frontiers in cardiovascular medicine · 2024Article
- Association between insulin resistance and uncontrolled hypertension and arterial stiffness among US adults: a population-based study.Cardiovascular diabetology · 2023Article
- Instantaneous detection of acute myocardial infarction and ischaemia from a single carotid pressure waveform in rats.European heart journal open · 2023Article
- Non-Invasive Pressure-Only Aortic Wave Intensity Evaluation Using Hybrid Fourier Decomposition-Machine Learning Approach.IEEE transactions on bio-medical engineering · 2023Article
- Screening left ventricular systolic dysfunction in children using intrinsic frequencies of carotid pressure waveforms measured by a novel smartphone-based device.Physiological measurement · 2023Article
- Central Arterial Dynamic Evaluation from Peripheral Blood Pressure Waveforms Using CycleGAN: An In Silico Approach.Sensors (Basel, Switzerland) · 2023Article
- A learning-based image processing approach for pulse wave velocity estimation using spectrogram from peripheral pulse wave signals: AnFrontiers in physiology · 2023Article
- Article
- Abdominal aortic aneurysm monitoring via arterial waveform analysis: towards a convenient point-of-care device.NPJ digital medicine · 2022Article
- Leveraging the potential of machine learning for assessing vascular ageing: state-of-the-art and future research.European heart journal. Digital health · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.
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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 Socratic graph.