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Prediction of Diabetes Mellitus: Comparative Study of Various Machine Learning Models

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1166))

Abstract

Diabetes is a common metabolic-cum-endocrine disorder in the world today. It is generally a chronic problem where either the pancreas does not produce an adequate quantity of Insulin, a hormone that regulates blood glucose level, or the body does not effectively utilize the produced Insulin. This review paper presents a comparison of various Machine Learning models in the detection of Diabetes Mellitus (Type-2 Diabetes). Selected papers published from 2010 to 2019 have been comparatively analyzed and conclusions were drawn. Various models that have been compared are Adaptive Neuro-Fuzzy Inference System (ANFIS), Deep Neural Network (DNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Logistic Regression, Decision Tree, Naive Bayes, K-Nearest Neighbours (KNN) and Random Forest. The two models which have outperformed all others in most studies taken into consideration are Random Forest and Naive Bayes. Other powerful mechanisms are SVM, ANN and ANFIS. The criteria chosen for comparison are accuracy and Matthew’s Correlation Coefficient (MCC).

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, 110062, India

    Arooj Hussain & Sameena Naaz

Authors
  1. Arooj Hussain
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  2. Sameena Naaz
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Corresponding author

Correspondence to Sameena Naaz .

Editor information

Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. CHRIST (Deemed to be University), Bengaluru, Karnataka, India

    Siddhartha Bhattacharyya

  4. Department of Information Technology, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  5. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Rohini, Delhi, India

    Sameer Anand

  6. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Rohini, Delhi, India

    Ajay Jaiswal

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Hussain, A., Naaz, S. (2021). Prediction of Diabetes Mellitus: Comparative Study of Various Machine Learning Models. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1166. Springer, Singapore. https://doi.org/10.1007/978-981-15-5148-2_10

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