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An Assessment of Type-2 Diabetes Risk Prediction Using Machine Learning Techniques

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Proceedings of International Conference on Big Data, Machine Learning and their Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 150))

Abstract

Diabetes is a metabolic chronic disease that due to the lack of insulin makes a serious problem with the transfer of blood all over the body. Nowadays, this epidemic has been expanding steadily everywhere throughout the world. Furthermore, negligence can lead to visual deficiency, amputations, cardiovascular breakdown, heart failure, and stroke. Diabetes generally occurs in two types (diabetes Type-1, diabetes Type-2) through the body, diabetes Type-2 shows the acute condition in the patient's body. The present study reviews the existing research studies and their methods for predicting diabetes using machine learning techniques, these methods use previously stored patient information to predict the next steps or the next events. During this research that using machine learning methods in addition to high speed and accuracy in the prediction of diabetes, it can improve the efficiency and importance of this process.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India

    Hardeep Kour & Darpan Anand

  2. School of Computing Science and Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India

    Munish Sabharwal

  3. Faculty of Digital Technologies, Samarkand State University, Samarkand, Uzbekistan

    Shakhzod Suvanov

Authors
  1. Hardeep Kour
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  2. Munish Sabharwal
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  3. Shakhzod Suvanov
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  4. Darpan Anand
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Corresponding author

Correspondence to Hardeep Kour .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  2. Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

    Erma Suryani

  3. Singapore Institute of Technology, Singapore, Singapore

    Andrew Keong Ng

  4. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh, India

    K. K. Mishra

  5. Department of Electrical Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh, India

    Nitin Singh

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Kour, H., Sabharwal, M., Suvanov, S., Anand, D. (2021). An Assessment of Type-2 Diabetes Risk Prediction Using Machine Learning Techniques. In: Tiwari, S., Suryani, E., Ng, A.K., Mishra, K.K., Singh, N. (eds) Proceedings of International Conference on Big Data, Machine Learning and their Applications. Lecture Notes in Networks and Systems, vol 150. Springer, Singapore. https://doi.org/10.1007/978-981-15-8377-3_10

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