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Type 2 diabetes data classification using stacked autoencoders in deep neural networks

  • Published:2019-12 Issue:4 Volume:7 Page:530-535
  • ISSN:2213-3984
  • Container-title:Clinical Epidemiology and Global Health
  • language:en
  • Short-container-title:Clinical Epidemiology and Global Health

Author:

Kannadasan K,Edla Damodar Reddy,Kuppili Venkatanareshbabu

Publisher

Elsevier BV

Subject

Infectious Diseases,Microbiology (medical),Public Health, Environmental and Occupational Health,Epidemiology

Reference29 articles.

1. The diagnostics of diabetes mellitus based on ensemble modeling and hair/urine element level analysis;Chen;Comput Biol Med,2014

2. Predicting type 2 diabetes using an electronic nose-based artificial neural network analysis;Mohamed;Diabetes, nutrition & metabolism,2002

3. An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease;Polat;Digit Signal Process,2007

4. Global Statistics Reports on NCDs;World Health Organization,2016

5. Spider monkey based rule miner using novel fitness function for diabetes classification;Cheruku;Comput Biol Med,2017

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