IDEAS home Printed from https://ideas.repec.org/a/igg/jhisi0/v16y2021i4p1-12.html
   My bibliography  Save this article

An Empirical Comparative Analysis Using Machine Learning Techniques for Liver Disease Prediction

Author

Listed:
  • Mohammed Alghobiri

    (King Khalid University, Abdha, Saudi Arabia)

  • Hikmat Ullah Khan

    (COMSATS University Islamabad, Pakistan)

  • Ahsan Mahmood

    (COMSATS University Islamabad, Pakistan)

Abstract

The human liver is one of the major organs in the body and liver disease can cause many problems in human live. Due to the increase in liver disease, various data mining techniques are proposed by the researchers to predict the liver disease. These techniques are improving day by day in order to predict and diagnose the liver disease in human. In this paper, real-world liver disease dataset is incorporated for diagnosing liver disease in human body. For this purpose, feature selection models are used to select a number of features that best are the most important feature to diagnose the liver disease. After selecting features and splitting data for training and testing, different classification algorithms in terms of naïve Bayes, supervised vector machine, decision tree, k near neighbor and logistic regression models to diagnose the liver disease in human body. The results are cross-validated by tenfold cross validation methods and achieve an accuracy as good as 93%.

Suggested Citation

  • Mohammed Alghobiri & Hikmat Ullah Khan & Ahsan Mahmood, 2021. "An Empirical Comparative Analysis Using Machine Learning Techniques for Liver Disease Prediction," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 16(4), pages 1-12, October.
    • Handle: RePEc:igg:jhisi0:v:16:y:2021:i:4:p:1-12
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJHISI.20211001.oa10
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Moina Ajmeri & Ahmad Ali, 2017. "Analytical design of modified Smith predictor for unstable second-order processes with time delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(8), pages 1671-1681, June.
    2. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, 2018. "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(1), January.
    3. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    4. P.R. Ouyang & V. Pano & T. Dam, 2015. "PID position domain control for contour tracking," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(1), pages 111-124, January.
    5. M. Kang & J. Cheong & H.M. Do & Y. Son & S.-I. Niculescu, 2017. "A practical iterative PID tuning method for mechanical systems using parameter chart," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(13), pages 2887-2900, October.
    6. Md. Majharul Haque & Suraiya Pervin & Anowar Hossain & Zerina Begum, 2020. "Approaches and Trends of Automatic Bangla Text Summarization: Challenges and Opportunities," International Journal of Technology Diffusion (IJTD), IGI Global, vol. 11(4), pages 67-83, October.
    7. Mourad Kchaou & Ahmed El-Hajjaji, 2017. "Resilient sliding mode control for discrete-time descriptor fuzzy systems with multiple time delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(2), pages 288-301, January.
    8. Changyin Sun & Qing Wang & Yao Yu, 2017. "Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(6), pages 1173-1181, April.
    9. Hassan Ghiti Sarand & Bahram Karimi, 2016. "Synchronisation of high-order MIMO nonlinear systems using distributed neuro-adaptive control," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(9), pages 2214-2224, July.
    10. Zhouhua Peng & Dan Wang & Gang Sun & Hao Wang, 2014. "Distributed cooperative stabilisation of continuous-time uncertain nonlinear multi-agent systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(10), pages 2031-2041, October.
    11. Bömmel, Nadja & Heineck, Guido, 2020. "Revisiting the Causal Effect of Education on Political Participation and Interest," IZA Discussion Papers 13954, Institute of Labor Economics (IZA).
    12. Zhengmin Liu & Peide Liu, 2017. "Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple attribute decision-making," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(5), pages 1092-1105, April.
    13. Herbon, Avi, 2021. "An integrated manufacturer-buyer chain with bounded production cycle length," Operations Research Perspectives, Elsevier, vol. 8(C).
    14. Olivier Cailloux & Tommi Tervonen & Boris Verhaegen & François Picalausa, 2014. "A data model for algorithmic multiple criteria decision analysis," Annals of Operations Research, Springer, vol. 217(1), pages 77-94, June.
    15. R. Sakthivel & V. Nithya & Yong-Ki Ma & Chao Wang, 2018. "Finite-Time Nonfragile Dissipative Filter Design for Wireless Networked Systems with Sensor Failures," Complexity, Hindawi, vol. 2018, pages 1-13, October.
    16. Hasan Salih Suliman Al-Qudah, 2016. "Application Level of Internal Audit Systems applied at Government Hospitals in North of Jordan," International Journal of Business and Management, Canadian Center of Science and Education, vol. 11(12), pages 187-187, November.
    17. Long Cheng & Hanlei Wang & Zeng-Guang Hou & Min Tan, 2016. "Reaching a consensus in networks of high-order integral agents under switching directed topologies," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(8), pages 1966-1981, June.
    18. Zhang-peng Tian & Hong-yu Zhang & Jing Wang & Jian-qiang Wang & Xiao-hong Chen, 2016. "Multi-criteria decision-making method based on a cross-entropy with interval neutrosophic sets," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(15), pages 3598-3608, November.
    19. Carlos Bianchi & Pablo Galaso & Sergio Palomeque, 2020. "Invention and Collaboration Networks in Latin America: Evidence from Patent Data," Documentos de Trabajo (working papers) 20-04, Instituto de Economía - IECON.
    20. Burcu Yılmaz Kaya & Aylin Adem & Metin Dağdeviren, 2020. "A DSS-Based Novel Approach Proposition Employing Decision Techniques for System Design," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 413-445, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jhisi0:v:16:y:2021:i:4:p:1-12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.