AIMC Topic: Blood Pressure

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Non-invasive blood pressure monitoring using wearables for cardiovascular risk assessment: a systematic review.

Archives of gynecology and obstetrics
PURPOSE: Cardiovascular diseases are the leading causes of mortality in women worldwide, with hypertension being a major risk factor. While traditional blood pressure monitoring techniques rely on cuff-based measurements, wearable devices offer a pro...

Diagnosis of chronic fatigue syndrome using beat-to-beat autonomic measurements.

Journal of translational medicine
BACKGROUND: An artificial intelligence (AI) pipeline was used to differentiate patients suffering from Chronic Fatigue Syndrome (CFS) from healthy controls (HC) based on high-frequency, large-scale data obtained using beat-to-beat measurement of the ...

Hemodynamic determinants of postoperative neurocognitive impairment using Random Forest analysis and partial dependence plots.

Scientific reports
This study investigated the effect of hemodynamic data during cardiopulmonary bypass (CPB) on neurocognitive impairment in patients undergoing coronary artery bypass graft (CABG) surgery using machine learning algorithms. Twenty-eight CABG patients w...

Advancing post-stroke blood pressure management: an individualized BP strategy for function optimization.

Annals of medicine
BACKGROUND: Stroke remains a major global public health concern and a leading cause of death, disability, and dementia. Despite being the most important and modifiable risk factor for stroke, Blood pressure (BP) management remain controversial and ch...

Evaluating the Clinical Effectiveness and Patient Experience of a Large Language Model-Based Digital Tool for Home-Based Blood Pressure Management: Mixed Methods Study.

JMIR mHealth and uHealth
BACKGROUND: Hypertension, one of the most common cardiovascular conditions worldwide, necessitates comprehensive management due to its association with multiple health risks. Effective control often involves lifestyle changes and continuous monitorin...

Non-linear interactions between intraocular, intracranial pressure and the retinal vascular pulse amplitude in the Fourier domain.

Scientific reports
The low explanatory power of a mixed effects linear model in evaluating interactions between retinal vascular pulse amplitude, intraocular pressure, and intracranial pressure suggests that these interactions are driven by non-linear dynamics. However...

Applying spectral analysis to the arterial pulse to discriminate cardiovascular side effects following administration of Moderna's mRNA-1273 vaccine.

European journal of pharmacology
Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have demonstrated strong efficacy in preventing symptomatic disease, but adverse cardiovascular side effects have been reported. This study investigated whether noninvasive...

Machine learning predictive system to predict the risk of developing pre-eclampsia.

BMJ health & care informatics
OBJECTIVES: To develop a machine learning (ML)-based predictive model for assessing the risk of pre-eclampsia using routinely collected clinical data.

Data-driven identification of key predictors of uncontrolled hypertension: A cross-sectional study.

PloS one
Uncontrolled hypertension (HTN) increases the risk of adverse health events. This study aimed to identify key predictors of uncontrolled HTN in 1,308 Mexican adults with a prior diagnosis of HTN who were undergoing pharmacological treatment. We utili...

Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records.

Scientific reports
Heart failure (HF) is a condition with periods of stability interrupted by periods of worsening symptoms, known as decompensation episodes. Digital interventions are promising tools to alleviate burdens on HF management through automated alerts at th...