K. Vidya Sudarshan

According to our database1, K. Vidya Sudarshan authored at least 24 papers between 2015 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals.
Computer Methods and Programs in Biomedicine, 2018

2017
Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals.
Neural Computing and Applications, 2017

Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal.
Knowl.-Based Syst., 2017

Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study.
Inf. Sci., 2017

Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2 s of ECG signals.
Comp. in Bio. and Med., 2017

Automated detection of premature delivery using empirical mode and wavelet packet decomposition techniques with uterine electromyogram signals.
Comp. in Bio. and Med., 2017

Shear wave elastography for characterization of breast lesions: Shearlet transform and local binary pattern histogram techniques.
Comp. in Bio. and Med., 2017

Application of higher-order spectra for the characterization of Coronary artery disease using electrocardiogram signals.
Biomed. Signal Proc. and Control, 2017

Data mining framework for breast lesion classification in shear wave ultrasound: A hybrid feature paradigm.
Biomed. Signal Proc. and Control, 2017

Characterization of Cardiovascular Diseases Using Wavelet Packet Decomposition and Nonlinear Measures of Electrocardiogram Signal.
Proceedings of the Advances in Artificial Intelligence: From Theory to Practice, 2017

2016
Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads.
Knowl.-Based Syst., 2016

An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images.
Information Fusion, 2016

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).
Comp. in Bio. and Med., 2016

Application of wavelet techniques for cancer diagnosis using ultrasound images: A Review.
Comp. in Bio. and Med., 2016

An integrated index for automated detection of infarcted myocardium from cross-sectional echocardiograms using texton-based features (Part 1).
Comp. in Bio. and Med., 2016

Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images.
Comp. in Bio. and Med., 2016

Sudden cardiac death (SCD) prediction based on nonlinear heart rate variability features and SCD index.
Appl. Soft Comput., 2016

Automated characterization of arrhythmias using nonlinear features from tachycardia ECG beats.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

2015
Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method.
Knowl.-Based Syst., 2015

An integrated index for detection of Sudden Cardiac Death using Discrete Wavelet Transform and nonlinear features.
Knowl.-Based Syst., 2015

Application of entropies for automated diagnosis of epilepsy using EEG signals: A review.
Knowl.-Based Syst., 2015

Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm.
Knowl.-Based Syst., 2015

Computer-aided diagnosis of Myocardial Infarction using ultrasound images with DWT, GLCM and HOS methods: A comparative study.
Comp. in Bio. and Med., 2015

Automated Prediction of Sudden Cardiac Death Risk Using Kolmogorov Complexity and Recurrence Quantification Analysis Features Extracted from HRV Signals.
Proceedings of the 2015 IEEE International Conference on Systems, 2015


  Loading...