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Artificial Intelligence Techniques for Predicting Type 2 Diabetes

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Advances in Artificial Intelligence and Data Engineering (AIDE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1133))

Abstract

Diabetes is the most common disease experienced recently. Type 1 diabetes, type 2 diabetes, and gestational diabetes are the most common types of diabetes. The aim is to predict the type 2 diabetes with various parameters. “Diabetes risk score or test system” is designed with the various risk factors like age, waist circumference, physical activity, family history, and BMI using artificial intelligence technique and to design a universally acceptable diabetes prediction system that predicts the possibility of diabetes risk. This process is carried out using the various parameters of the patient’s lifestyle and without using the data from medical test results. The individuals who are interested to know about their risk score can use this diabetes risk score system.

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Authors and Affiliations

  1. NMAM Institute of Technology, Nitte, Udupi, Karnataka, 574110, India

    Ramyashree, P. S. Venugopala & B. Ashwini

  2. Nitte University Centre for Science Education and Research, Paneer Rd, Kotekar, Mangalore, Karnataka, India

    Debmalya Barh

Authors
  1. Ramyashree
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  2. P. S. Venugopala
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  3. Debmalya Barh
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  4. B. Ashwini
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Corresponding author

Correspondence to Ramyashree .

Editor information

Editors and Affiliations

  1. NMAM Institute of Technology, Udupi, India

    Niranjan N. Chiplunkar

  2. Ritsumeikan University, Shiga, Japan

    Takanori Fukao

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Ramyashree, Venugopala, P.S., Barh, D., Ashwini, B. (2021). Artificial Intelligence Techniques for Predicting Type 2 Diabetes. In: Chiplunkar, N.N., Fukao, T. (eds) Advances in Artificial Intelligence and Data Engineering. AIDE 2019. Advances in Intelligent Systems and Computing, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-15-3514-7_32

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