AIMC Topic: Blood Pressure

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Machine Learning and Artificial Intelligence for Research on Hypertension.

American journal of hypertension
Hypertension continues to be the leading modifiable risk factor for mortality globally, contributing significantly to cardiovascular disease. The American Heart Association (AHA) 2017 Hypertension Guidelines define hypertension as blood pressure (BP)...

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
Myocardial infarction (MI) is a leading cause of death worldwide and the most common precursor to heart failure, even after initial treatment. Precise evaluation of myocardial injury is crucial for assessing interventions and improving outcomes. Exte...

Association between prenatal exposure to per- and polyfluoroalkyl substances and blood pressure among preschool-aged children: The moderating effect of child-age and the mediating effect of inflammatory cytokine.

Ecotoxicology and environmental safety
Our aim is to evaluate the association of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with offspring blood pressure (BP); examine the moderating effect of children's age; and the mediating effects of inflammatory cytokines. Data o...

Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.

Ecotoxicology and environmental safety
BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence indicates that the key biological processes of oxidative stress, inflammation, and endothelial dysfunct...

Artificial Intelligence to Improve Blood Pressure Control: A State-of-the-Art Review.

American journal of hypertension
Hypertension remains a major global health challenge, contributing to significant morbidity and mortality. Advances in artificial intelligence (AI) and machine learning (ML) are transforming hypertension care by enhancing blood pressure (BP) measurem...

Metabolomic machine learning predictor for arsenic-associated hypertension risk in male workers.

Journal of pharmaceutical and biomedical analysis
Arsenic (As)-induced hypertension is a significant public health concern, highlighting the need for early risk prediction. This study aimed to develop a predictive model for occupational As exposure and hypertension using metabolomics and machine lea...

Predicting blood pressure without a cuff using a unique multi-modal wearable device and machine learning algorithm.

Computers in biology and medicine
Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not monitor it frequently enough to prevent serious complications. This is in part because the traditional cuff-based method is inconvenient, uncomfortabl...

Investigating the correlation between smoking and blood pressure via photoplethysmography.

Biomedical engineering online
Smoking has been widely identified for its detrimental effects on human health, particularly on the cardiovascular health. The prediction of these effects can be anticipated by monitoring the dynamic changes in vital signs and other physiological sig...

Detection of atrial fibrillation from pulse waves using convolution neural networks and recurrence-based plots.

Chaos (Woodbury, N.Y.)
We propose a classification method for distinguishing atrial fibrillation from sinus rhythm in pulse-wave measurements obtained with a blood pressure monitor. This method combines recurrence-based plots with convolutional neural networks. Moreover, w...