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Disease Detection and Prediction Using the Liver Function Test Data: A Review of Machine Learning Algorithms

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1388))

Abstract

In the last decade, there has been an admirable improvement in the classification accuracy of various machine learning techniques used for disease diagnosis. This even aids in finding the associations and patterns in the data, which helps in the construction of prediction model. Diagnosing illness by considering the features that have the maximum impact on recognition is important to control the disease. The main objective of this research paper is to provide a summarized review of literature with comparative results, which has been done for the detection and prediction of liver diseases with various machine learning algorithms using the liver function test data in order to make the analytical conclusions. From this study, it is observed that the CMAC, RBF, PSO-LS-SVM and ADTree improve the accuracy of liver disease detection and prediction. A review of past findings on the LFT data and its association with diabetes prediction is also studied.

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, University of Kashmir, Srinagar, J&K, India

    Ifra Altaf & Muheet Ahmed Butt

  2. Directorate of IT&SS, University of Kashmir, Srinagar, J&K, India

    Majid Zaman

Authors
  1. Ifra Altaf
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  2. Muheet Ahmed Butt
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  3. Majid Zaman
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Editor information

Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, Delhi, India

    Ashish Khanna

  2. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  3. Rajnagar Mahavidyalaya, Birbhum, India

    Siddhartha Bhattacharyya

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

    Aboul Ella Hassanien

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

    Sameer Anand

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

    Ajay Jaiswal

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Altaf, I., Butt, M.A., Zaman, M. (2022). Disease Detection and Prediction Using the Liver Function Test Data: A Review of Machine Learning Algorithms. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1388. Springer, Singapore. https://doi.org/10.1007/978-981-16-2597-8_68

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