Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges
SK Saini, R Gupta - Artificial Intelligence Review, 2022 - Springer
Abstract Cardiovascular diseases (CVDs) in India and globally are the major cause of
mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace …
mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace …
A review of automated methods for detection of myocardial ischemia and infarction using electrocardiogram and electronic health records
There is a growing body of research focusing on automatic detection of ischemia and
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …
[图书][B] Time series clustering and classification
The beginning of the age of artificial intelligence and machine learning has created new
challenges and opportunities for data analysts, statisticians, mathematicians …
challenges and opportunities for data analysts, statisticians, mathematicians …
[HTML][HTML] Review of dimension reduction methods
Purpose: This study sought to review the characteristics, strengths, weaknesses variants,
applications areas and data types applied on the various Dimension Reduction techniques …
applications areas and data types applied on the various Dimension Reduction techniques …
A new personalized ECG signal classification algorithm using block-based neural network and particle swarm optimization
S Shadmand, B Mashoufi - Biomedical Signal Processing and Control, 2016 - Elsevier
The purpose of this paper is the classification of ECG heartbeats of a patient in five heartbeat
types according to AAMI recommendation, using an artificial neural network. In this paper a …
types according to AAMI recommendation, using an artificial neural network. In this paper a …
Evaluation of handcrafted features and learned representations for the classification of arrhythmia and congestive heart failure in ECG
Electrocardiogram (ECG) is considered as an essential diagnostic tool to investigate life-
threatening cardiac abnormalities, such as arrhythmia and congestive heart failure. It is …
threatening cardiac abnormalities, such as arrhythmia and congestive heart failure. It is …
Novel machine-learning based framework using electroretinography data for the detection of early-stage glaucoma
MK Gajendran, LJ Rohowetz, P Koulen… - Frontiers in …, 2022 - frontiersin.org
Purpose Early-stage glaucoma diagnosis has been a challenging problem in
ophthalmology. The current state-of-the-art glaucoma diagnosis techniques do not …
ophthalmology. The current state-of-the-art glaucoma diagnosis techniques do not …
Robust and accurate anomaly detection in ECG artifacts using time series motif discovery
H Sivaraks, CA Ratanamahatana - … and mathematical methods …, 2015 - Wiley Online Library
Electrocardiogram (ECG) anomaly detection is an important technique for detecting
dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process …
dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process …
Wavelet-based fuzzy clustering of interval time series
We investigate the fuzzy clustering of interval time series using wavelet variances and
covariances; in particular, we use a fuzzy c-medoids clustering algorithm. Traditional …
covariances; in particular, we use a fuzzy c-medoids clustering algorithm. Traditional …
Real-life stress level monitoring using smart bands in the light of contextual information
An automatic stress detection system that uses unobtrusive smart bands will contribute to
human health and well-being by alleviating the effects of high stress levels. However, there …
human health and well-being by alleviating the effects of high stress levels. However, there …