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Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease

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Proceedings of International Conference on Data Science and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 148))

Abstract

Prior identification is an important factor in controlling the chronic kidney disease (CKD). The clinical data and diagnostic results provide concealed facts which will help physicians to identify severity of CKD. In this paper, we propose a fuzzy analytical hierarchy process-based model for detecting CKD. In addition, a mobile app has been developed for collecting data from patient. The performance evaluation shows that relatively high accuracy can be achieved through the proposed method.

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Author information

Authors and Affiliations

  1. Department of Information and Communication Engineering, Bangladesh University of Professionals, Dhaka, Bangladesh

    Zarin Subah Shamma, Israt Jahan Rumman, Ali Mual Raji Saikot, S. M. Salim Reza & Md. Maynul Islam

  2. Computing & Technology, Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  3. Institute of Information Technology, Jahangirnagar University, Dhaka, 1342, Bangladesh

    M. Shamim Kaiser

Authors
  1. Zarin Subah Shamma
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  2. Israt Jahan Rumman
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  3. Ali Mual Raji Saikot
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  4. S. M. Salim Reza
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  5. Md. Maynul Islam
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  6. Mufti Mahmud
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  7. M. Shamim Kaiser
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Corresponding author

Correspondence to M. Shamim Kaiser .

Editor information

Editors and Affiliations

  1. Amity School of Applied Sciences, Amity University Rajasthan, Jaipur, Rajasthan, India

    Kanad Ray

  2. Kautilya Institute of Technology and Engineering, Jaipur, Rajasthan, India

    Krishna Chandra Roy

  3. Kautilya Institute of Technology and Engineering, Jaipur, Rajasthan, India

    Sandeep Kumar Toshniwal

  4. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  5. Surface Characterization Group, Nano Characterization Unit, Advanced Key Technologies Division, National Institute for Materials Science, Tsukuba, Japan

    Anirban Bandyopadhyay

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Shamma, Z.S. et al. (2021). Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease. In: Ray, K., Roy, K.C., Toshniwal, S.K., Sharma, H., Bandyopadhyay, A. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, vol 148. Springer, Singapore. https://doi.org/10.1007/978-981-15-7561-7_7

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