Systole - AI Medical Compendium

Automatic Onsets and Systolic Peaks Detection and Segmentation of Arterial Blood Pressure Waveforms using Fully Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021

Arterial blood pressure (ABP) waveform is a common physiological signal that contains a wealth of cardiovascular information. According to the cardiac cycle, the ABP waveform is divided into rapid ejection, systolic and diastolic phases. Therefore, t...

Neural Networks, Computer Arterial Pressure Systole Humans

View on PubMed DOI

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

International heart journal Jan 1, 2021

Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep learning model may improve the diagnostic accuracy of cardiologists in predicting LV dysfunction from E...

Electrocardiography Ventricular Dysfunction, Left Aged, 80 and over Systole Humans Adult Deep Learning Decision Support Systems, Clinical Female Aged Cardiologists Male Sensitivity and Specificity Middle Aged

View on PubMed DOI

Blood Pressure Estimation Using Time Domain Features of Auscultatory Waveforms and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019

This paper presents a novel method to estimate systolic blood pressure (SBP) and diastolic blood pressure (DBP) from time domain features extracted on auscultatory waveforms (AWs) using a long short term memory (LSTM) recurrent neural network (RNN). ...

Neural Networks, Computer Deep Learning Blood Pressure Determination Humans Blood Pressure Systole

View on PubMed DOI

An unsupervised learning for robust cardiac feature derivation from PPG signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016

We propose here derivation algorithms for physiological parameters like beat start point, systolic peak, pulse duration, peak-to-peak distance related to heart rate, dicrotic minima, diastolic peak from Photoplethysmogram (PPG) signals robustly. Our ...

Signal Processing, Computer-Assisted Heart Rate Systole Photoplethysmography Unsupervised Machine Learning Diastole Humans Algorithms

View on PubMed DOI

Effects of tibial intraosseous and intravenous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

American journal of disaster medicine Jan 1, 2016

OBJECTIVE: To determine if there were significant differences between the tibial intraosseous (TIO) and intravenous (IV) administration of Hextend relative to time and in hemodynamics in a hypovolemic model.

Infusions, Intraosseous Shock Diastole Tibia Plasma Substitutes Arterial Pressure Hypovolemia Male Fluid Therapy Random Allocation Systole Swine Prospective Studies Sus scrofa Stroke Volume Heart Rate Animals Treatment Outcome Hemodynamics Hydroxyethyl Starch Derivatives Time Factors Cardiac Output Infusions, Intravenous

View on PubMed DOI

Effects of intravenous, sternal, and humerus intraosseous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

American journal of disaster medicine Jan 1, 2016

OBJECTIVE: To determine if there were significant differences among humerus intraosseous (HIO), sternal intraosseous (SIO), and intravenous (IV) administration of 500 mL Hextend in hemodynamics or administration time in a hypovolemic swine model.

Sternum Diastole Humerus Animals Plasma Substitutes Male Hypovolemia Sus scrofa Swine Infusions, Intraosseous Hydroxyethyl Starch Derivatives Hemodynamics Stroke Volume Heart Rate Shock Prospective Studies Infusions, Intravenous Cardiac Output Treatment Outcome Blood Pressure Random Allocation Systole Fluid Therapy Disease Models, Animal

View on PubMed DOI

AIMC Topic: Systole

Automatic Onsets and Systolic Peaks Detection and Segmentation of Arterial Blood Pressure Waveforms using Fully Convolutional Neural Networks.

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

Blood Pressure Estimation Using Time Domain Features of Auscultatory Waveforms and Deep Learning.

An unsupervised learning for robust cardiac feature derivation from PPG signals.

Effects of tibial intraosseous and intravenous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

Effects of intravenous, sternal, and humerus intraosseous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

Popular Topics

Recent Journals

AIMC Topic: Systole

Automatic Onsets and Systolic Peaks Detection and Segmentation of Arterial Blood Pressure Waveforms using Fully Convolutional Neural Networks.

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

Blood Pressure Estimation Using Time Domain Features of Auscultatory Waveforms and Deep Learning.

An unsupervised learning for robust cardiac feature derivation from PPG signals.

Effects of tibial intraosseous and intravenous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

Effects of intravenous, sternal, and humerus intraosseous administration of Hextend on time of administration and hemodynamics in a hypovolemic swine model.

Don't Miss the Future of Medicine

Popular Topics

Recent Journals