AIMC Topic: Blood Pressure

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Predicting blood pressure from face videos using face diagnosis theory and deep neural networks technique.

Computers in biology and medicine
Hypertension is a major cause of cardiovascular diseases. Accurate and convenient measurement of blood pressure are necessary for the detection, treatment, and control of hypertension. In recent years, face video based non-contact blood pressure pred...

A Deep Learning Framework for Deriving Noninvasive Intracranial Pressure Waveforms from Transcranial Doppler.

Annals of neurology
Increased intracranial pressure (ICP) causes disability and mortality in the neurointensive care population. Current methods for monitoring ICP are invasive. We designed a deep learning framework using a domain adversarial neural network to estimate ...

A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography.

Physiological measurement
. The aim of this study is to investigate continuous blood pressure waveform estimation from a plethysmography (PPG) signal, thus providing more human cardiovascular status information than traditional cuff-based methods.. The proposed method utilize...

Survey and Evaluation of Hypertension Machine Learning Research.

Journal of the American Heart Association
Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision-making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studie...

Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.

PloS one
INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The fie...

Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm.

International journal of environmental research and public health
Few studies classified and predicted hypertension using blood pressure (BP)-related determinants in a deep learning algorithm. The objective of this study is to develop a deep learning algorithm for the classification and prediction of hypertension w...

Data-Driven Guided Attention for Analysis of Physiological Waveforms With Deep Learning.

IEEE journal of biomedical and health informatics
Estimating physiological parameters - such as blood pressure (BP) - from raw sensor data captured by noninvasive, wearable devices rely on either burdensome manual feature extraction designed by domain experts to identify key waveform characteristics...

Machine-Learning Classification of Pulse Waveform Quality.

Sensors (Basel, Switzerland)
Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor ...

Detection of the Relationship between the Multi-Dimensional Data Sets of Serially Measured Blood Pressure and the Future Risk of Death in Healthy Elderly Japanese Population.

Journal of atherosclerosis and thrombosis
AIMS: Whether the multi-dimensional data of serially measured blood pressure contains information for predicting the future risk of death in elderly individuals in nursing homes is unclear.

Classification and regression of stenosis using an in-vitro pulse wave data set: Dependence on heart rate, waveform and location.

Computers in biology and medicine
BACKGROUND: Data-based approaches promise to use the information in cardiovascular signals to diagnose cardiovascular diseases. Considerable effort has been undertaken in the field of pulse-wave analysis to harness this information. However, the inve...