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A Robust Deep Learning Techniques for No-Show Prediction in Hospital Appointments

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Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023 (AISI 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 184))

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Abstract

Machine learning (ML) has been widely adopted in the healthcare industry for improving patient outcomes and operational efficiency. Predicting no-show appointments is one of the areas where ML has been applied to optimize appointment scheduling and management. However, there are still challenges to be addressed when applying ML to predict no-show appointments, including data quality and potential biases in the models. In recent years, deep learning (DL) has emerged as a powerful tool for solving complex problems, including those in the healthcare industry. This paper proposes a DL technique to predict no-show appointments in the hospital sector using a dataset of historical patient appointments and their attendance. The study aims to accurately predict which patients are at risk of not attending their appointments and explore ways to improve appointment scheduling and management using these predictions. The paper also discusses the benefits and challenges of using ML and DL methods in healthcare services and provides theoretical and managerial implications for future research and practice.

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Acknowledgment

The authors would like to thank Eastern International University (EIU) and Becamex International Hospital (BIH) Vietnam for funding this research.

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Authors and Affiliations

  1. Becamex Business School, Eastern International University, Thủ Dầu Một, Vietnam

    Phat Tien Nguyen

  2. Becamex International Hospital, Thuận An, Binh Duong, Vietnam

    Phat Tien Nguyen

  3. School of Computing and Information Technology, Eastern International University, Thủ Dầu Một, Vietnam

    Doan Thai Dang & Vinh Dinh Nguyen

Authors
  1. Phat Tien Nguyen
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  2. Doan Thai Dang
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  3. Vinh Dinh Nguyen
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Corresponding author

Correspondence to Vinh Dinh Nguyen .

Editor information

Editors and Affiliations

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

    AboulElla Hassanien

  2. Port Said University, Port Fouad City, Egypt

    Rawya Y. Rizk

  3. Department of Operations Research and Statistics, The University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia

    Dragan Pamucar

  4. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  5. Shulin District, Fujian University of Technology, New Taipei, Taiwan

    Kuo-Chi Chang

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Nguyen, P.T., Dang, D.T., Nguyen, V.D. (2023). A Robust Deep Learning Techniques for No-Show Prediction in Hospital Appointments. In: Hassanien, A., Rizk, R.Y., Pamucar, D., Darwish, A., Chang, KC. (eds) Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023. AISI 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-031-43247-7_1

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