This paper is in the following e-collection/theme issue:

Genetic engineering (2) Glucose Tracking and Self-Monitoring of Blood Glucose (162)

Published on in Vol 5, No 1 (2020): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20932, first published .
Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features

Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features

Diagnosis of Type 2 Diabetes Using Electrogastrograms: Extraction and Genetic Algorithm–Based Selection of Informative Features

Authors of this article:

Paramasivam Alagumariappan1 Author Orcid Image ;   Kamalanand Krishnamurthy2 Author Orcid Image ;   Sundravadivelu Kandiah3 Author Orcid Image ;   Emmanuel Cyril4 Author Orcid Image ;   Rajinikanth V5 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Paramasivam Alagumariappan   1 * , PhD ;   Kamalanand Krishnamurthy   2 * , PhD ;   Sundravadivelu Kandiah   3 * , MBBS ;   Emmanuel Cyril   4 * , PhD ;   Rajinikanth V   5 * , PhD

1 Department of Electrical and Electronics Engineering, Chennai, India

2 Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai, India

3 Shree Balaji Clinic, Ezhil Nagar, Selaiyur, Chennai, India

4 Global Hospitals & Health City, Cheran Nagar, Perumbakkam, Chennai, India

5 Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, India

*all authors contributed equally

Corresponding Author:

  • Paramasivam Alagumariappan, PhD
  • Department of Electrical and Electronics Engineering
  • B. S. Abdur Rahman Crescent Institute of Science and Technology,
  • Chennai, 600048
  • India
  • Phone: 91 9843780801
  • Email: parama.ice@gmail.com