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A Probit Regression in Identifying the Risk Factors of Cervical Cancer in Malaysian Private Hospital

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Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 348))

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Abstract

Cervical cancer is the second largest cancer listed as the major cause of death for women worldwide. Generalized linear models (GLMs) were conducted to identify the risk factor of cervical cancer and to build a suitable model. This research is to identify the risk factors and investigate the relationship between cervical cancer and some risk factors based on the 854 samples from the private hospital. Probit regression was used to identify the risk factors of cervical cancer. Out of seven independent variables, two variables were given a significant relationship with cervical cancer. There was a significant relationship between cervical cancer with age and STDs which the p-value is less than 0.05. Thus, age and STDs influence the presence of cervical cancer in a private hospital. Women who have older age are more likely to have cervical cancer. For the woman who had STDs, the probability will be higher compared with no had STDs. Preliminary analysis with some cross-tabulation analysis is presented in this research. The probit regression model was built and the prediction was predicted with different cases of observation and this is the main contribution of the paper. The risk of getting cervical cancer can be reduced effectively if women have more knowledge of cervical cancer and the risk factors of cervical cancer can be identified.

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Acknowledgements

Fundamental Research Grant Scheme (FRGS) No. K175 (FRGS/1/2019/STG06/UTHM/02/2) from the Ministry of Higher Education Malaysia (MOHE) and Universiti Tun Hussein Onn Malaysia (UTHM).

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Authors and Affiliations

  1. Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia, 84600, Pagoh, Johor, Malaysia

    Tan Li Jun & Suliadi F. Sufahani

  2. Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Johor, Malaysia

    Mohd Fahmy-Abdullah

  3. Oasis Integrated Group, Universiti Tun Hussein Onn Malaysia, Parit Raja, 86400, Batu Pahat, Johor, Malaysia

    Suliadi F. Sufahani & Mohd Fahmy-Abdullah

Authors
  1. Tan Li Jun
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  2. Suliadi F. Sufahani
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  3. Mohd Fahmy-Abdullah
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Corresponding author

Correspondence to Suliadi F. Sufahani .

Editor information

Editors and Affiliations

  1. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  2. Amity University Rajasthan, Jaipur, India

    Kanad Ray

  3. Surface Characterization Group, National Institute for Materials Science, Tsukuba, Japan

    Anirban Bandyopadhyay

  4. Faculty of Applied Sciences and Technology, Tun Hussein Onn University of Malaysia, Parit Raja, Johor, Malaysia

    Kavikumar Jacob

  5. Faculty of Applied Sciences and Technology (FAST), Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Kek Sie Long

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Jun, T.L., Sufahani, S.F., Fahmy-Abdullah, M. (2022). A Probit Regression in Identifying the Risk Factors of Cervical Cancer in Malaysian Private Hospital. In: Kaiser, M.S., Ray, K., Bandyopadhyay, A., Jacob, K., Long, K.S. (eds) Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering. Lecture Notes in Networks and Systems, vol 348. Springer, Singapore. https://doi.org/10.1007/978-981-16-7597-3_14

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