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A Review for Predicting the Diabetes Mellitus Using Different Techniques and Methods

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Proceedings of International Conference on Data Science and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 288))

Abstract

The evaluation of computer-aided detection and diagnosis systems has become popular in all the major and important zones in the medical sciences. Early prediction of any disease required to be exact to protect human life. To achieve this goal, the intelligent systems based on some techniques which are capable to learn from previous experience and are found to be important tool for diagnosis and treatment planning of various diseases are being employed. Artificial intelligence, machine learning, and deep learning are among the key techniques which have fully revolutionized whole of science and hence the life. These provide efficient results to extract facts by developing the predicting models from diagnostic medical datasets along with the patient’s records. This paper provides a literature review on prediction of the diabetes mellitus (DM) and accuracy rate of the algorithms basically through these techniques involving supervised, unsupervised, and semi supervised learning algorithms. This paper puts spotlight on recent developments in machine and deep learning methods and techniques which have made significant impacts in the prediction and diagnosis of diabetes.

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Author information

Authors and Affiliations

  1. Chitkara University Institute of Engineering and Technology, Chitkara University, Chandigarh, Punjab, India

    Preeti Saini & Rakesh Ahuja

Authors
  1. Preeti Saini
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  2. Rakesh Ahuja
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Corresponding author

Correspondence to Preeti Saini .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Sarbani Roy

  3. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Chandreyee Chowdhury

  4. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia

    Amir H. Gandomi

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Saini, P., Ahuja, R. (2022). A Review for Predicting the Diabetes Mellitus Using Different Techniques and Methods. In: Saraswat, M., Roy, S., Chowdhury, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications . Lecture Notes in Networks and Systems, vol 288. Springer, Singapore. https://doi.org/10.1007/978-981-16-5120-5_32

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