Tag: cardiovascular
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ECG Early Warning System (EWS) in Terms of Time-Variant Deformations and Creep-Recovery Strain Tests
Featured Photo by Hernan Pauccara on Pexels Referring to an earlier stress-strain case study, the objective of this risk management project is to develop the ECG Early Warning System (EWS) based upon time-dependent viscoelastic deformations and observed creep-recovery mechanisms in the cardiac muscle. The creep-recovery test involves loading a material at constant stress, holding that…
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AI-Based ECG Recognition – EOY ’22 Status
Featured Photo by cottonbro studio on pexels. Electrocardiography (ECG) is the method most often used to diagnose cardiovascular diseases. The recent study demonstrates that an AI is capable of automatically diagnosing the abnormalities indicated by an ECG. In this post we will review and illustrate how AI applies to ECG analysis to outperform traditional ECG analysis.…
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DL-Assisted ECG/EKG Anomaly Detection using LSTM Autoencoder
This project implements an ECG anomaly detection framework using an LSTM Autoencoder to accurately identify abnormal ECG events. It trains the autoencoder on normal rhythms, using reconstruction errors to identify anomalies. The proposed method aims to improve abnormal ECG detection, as demonstrated by test results on the ECG5000 dataset, providing valuable information for patient health…
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HealthTech ML/AI Q3 ’22 Round-Up
Featured Photo by Andy Kelly on Unsplash This blog presents a Q3 ’22 summary of current healthtech ML/AI innovation methods, trends and challenges. Virtual reality, artificial intelligence, augmented reality, and machine learning are all healthcare technology trends that are going to play a vital role across the entire healthcare system. Let’s take a look at…
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