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Blood Pressure

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Minimally invasive monitor of cardiac output based on the machine-learning analysis of the pulse contour of the peripheral arterial pressure.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In the hemodynamic management of anesthetized patients during surgical operation, minimally invasive and accurate cardiac output (CO) monitoring is strongly required. We have developed a CO monitor based on the machine-learning analysis of the pulse ...

Machine Learning Algorithm to Estimate Cardiac Output Based On Less-Invasive Arterial Blood Pressure Measurements.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiac output (CO) is a vital hemodynamic parameter that reflects the blood volume pumped by the heart per minute. A less-invasive way to estimate CO is by analyzing arterial blood pressure (ABP) waveforms. However, the relationship between CO and b...

Advancing Cuffless Arterial Blood Pressure Waveform Estimation: Time-Series Deep Neural Network Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Existing deep learning models for arterial blood pressure (ABP) estimation are becoming increasingly complex. They mainly treat the estimation as a sequence-to-sequence (seq2seq) task, to establish the relationship between input physiological signals...

TO-LAB model: Real time Touchless Lung Abnormality detection model using USRP based machine learning algorithm.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Due to the increasing prevalence of respiratory diseases and the importance of early diagnosis. The need for non-invasive and touchless medical diagnostic solutions has become increasingly crucial in modern healthcare to detect lung abnor...

Prediction of intradialytic hypotension using pre-dialysis features-a deep learning-based artificial intelligence model.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: Intradialytic hypotension (IDH) is a serious complication of hemodialysis (HD) that is associated with increased risks of cardiovascular morbidity and mortality. However, its accurate prediction remains a clinical challenge. The aim of th...

Demographic Information Fusion Using Attentive Pooling In CNN-GRU Model For Systolic Blood Pressure Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fusing demographic information into deep learning models has become of interest in recent end-to-end cuff-less blood pressure (BP) estimation studies in order to achieve improved performance. Conventionally, the demographic feature vector is concaten...

An interpretable machine learning model for real-time sepsis prediction based on basic physiological indicators.

European review for medical and pharmacological sciences
OBJECTIVE: In view of the important role of risk prediction models in the clinical diagnosis and treatment of sepsis, and the limitations of existing models in terms of timeliness and interpretability, we intend to develop a real-time prediction mode...

A novel method for conformity assessment testing of patient monitors for post-market surveillance purposes.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Patient monitors are medical devices used to monitor vital parameters such as heart rate, respiratory rate, blood pressure, blood oxygen saturation, and body temperature during inpatient treatment. As such, patient monitors provide physic...

Application of Combined Prediction Model Based on Core and Coritivity Theory in Continuous Blood Pressure Prediction.

Combinatorial chemistry & high throughput screening
BACKGROUND AND OBJECTIVE: Blood pressure is vital evidence for clinicians to predict diseases and check the curative effect of diagnosis and treatment. To further improve the prediction accuracy of blood pressure, this paper proposes a combined predi...