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Proceedings of International Joint Conference on Computational Intelligence pp 85–97Cite as

Diabetes Mellitus Risk Prediction Using Artificial Neural Network

Part of the Algorithms for Intelligent Systems book series (AIS)

Abstract

Diabetes is a non-communicable disease and various types of dangerous diseases like heart attack, kidney failure, myopia, and so on are caused by it. The number of people suffering from diabetes is increasing rapidly. Though there has no perpetual cure for diabetes, it can be controlled by proper counseling and medication. For this perception, an early determination is needed. In our analysis, 464 patients data with 23 features were collected from various health-care units and preprocessed. A predictive model was developed with artificial neural network technique. Different learning rate, hidden layers were applied in our analysis. Average-weighted accuracy of all observations was approximately 99.69%.

Keywords

  • Diabetes mellitus
  • Artificial neural network (ANN)
  • Machine learning
  • Type-1
  • Type-2
  • Risk factors

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Author information

Authors and Affiliations

  1. North Western University, Khulna, Bangladesh

    M. Raihan, Nasif Alvi, Md. Tanvir Islam, Fahmida Farzana & Md. Mahadi Hassan

  2. Khulna University, Khulna, Bangladesh

    Nasif Alvi & Md. Mahadi Hassan

  3. Khulna University of Engineering & Technology, Khulna, Bangladesh

    M. Raihan

Authors
  1. M. Raihan
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  2. Nasif Alvi
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  3. Md. Tanvir Islam
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  4. Fahmida Farzana
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  5. Md. Mahadi Hassan
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Corresponding author

Correspondence to M. Raihan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

    Dr. Mohammad Shorif Uddin

  2. Department of Mathematics, South Asian University, New Delhi, India

    Dr. Jagdish Chand Bansal

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Raihan, M., Alvi, N., Tanvir Islam, M., Farzana, F., Mahadi Hassan, M. (2020). Diabetes Mellitus Risk Prediction Using Artificial Neural Network. In: Uddin, M.S., Bansal, J.C. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-3607-6_7

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