AIMC Topic: Blood Pressure

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Recent developments in machine learning modeling methods for hypertension treatment.

Hypertension research : official journal of the Japanese Society of Hypertension
Hypertension is the leading cause of cardiovascular complications. This review focuses on the advancements in medical artificial intelligence (AI) models aimed at individualized treatment for hypertension, with particular emphasis on the approach to ...

Peripheral artery disease diagnosis based on deep learning-enabled analysis of non-invasive arterial pulse waveforms.

Computers in biology and medicine
This paper intends to investigate the feasibility of peripheral artery disease (PAD) diagnosis based on the analysis of non-invasive arterial pulse waveforms. We generated realistic synthetic arterial blood pressure (BP) and pulse volume recording (P...

A Systematic Approach Focused on Machine Learning Models for Exploring the Landscape of Physiological Measurement and Estimation Using Photoplethysmography (PPG).

Journal of cardiovascular translational research
A non-invasive optical technique known as photoplethysmography (PPG) can be used to provide various physiological measurements and estimations. PPG can be used to assess cardiovascular disease (CVD). Hypertension is a primary risk factor for CVD and ...

Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring.

ACS nano
A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since th...

A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring.

Nature biomedical engineering
The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline Clin...

Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.

Hypertension (Dallas, Tex. : 1979)
BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys i...

Analysis of intracranial pressure pulse waveform in studies on cerebrospinal compliance: a narrative review.

Physiological measurement
Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure-volume compensation, i.e. the ability of the cerebrospinal system to buffer changes in vol...

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Scientific reports
Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual outcomes in real-time has never been developed. Herein, we developed an explainable deep learning mo...

Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.

Physical and engineering sciences in medicine
The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate, and cardiac output. Continuous analysis of hemodynamic parameters such as BP can detect abnormalit...

As artificial intelligence goes multimodal, medical applications multiply.

Science (New York, N.Y.)
Machines don't have eyes, but you wouldn't know that if you followed the progression of deep learning models for accurate interpretation of medical images, such as x-rays, computed tomography (CT) and magnetic resonance imaging (MRI) scans, pathology...