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

Zarin Subah Shamma; Israt Jahan Rumman; Ali Mual Raji Saikot; S. M. Salim Reza; Md Maynul Islam; Mufti Mahmud; M. Shamim Kaiser

doi:10.1007/978-981-15-7561-7_7

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

Zarin Subah Shamma
, Israt Jahan Rumman
, Ali Mual Raji Saikot
, S. M. Salim Reza
, Md Maynul Islam
, Mufti Mahmud
, M. Shamim Kaiser^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

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.

Original language	English
Title of host publication	Lecture Notes in Networks and Systems
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	99-110
Number of pages	12
DOIs	https://doi.org/10.1007/978-981-15-7561-7_7
State	Published - 2021
Externally published	Yes

Publication series

Name	Lecture Notes in Networks and Systems
Volume	148
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Bibliographical note

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Fuzzy analytical hierarchy process
Kidney disease
Mobile App
Multicriteria decision making

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-15-7561-7_7

Cite this

Shamma, Z. S., Rumman, I. J., Raji Saikot, A. M., Salim Reza, S. M., Islam, M. M., Mahmud, M., & Shamim Kaiser, M. (2021). Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease. In Lecture Notes in Networks and Systems (pp. 99-110). (Lecture Notes in Networks and Systems; Vol. 148). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-7561-7_7

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title = "Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease",

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.",

keywords = "Fuzzy analytical hierarchy process, Kidney disease, Mobile App, Multicriteria decision making",

author = "Shamma, \{Zarin Subah\} and Rumman, \{Israt Jahan\} and \{Raji Saikot\}, \{Ali Mual\} and \{Salim Reza\}, \{S. M.\} and Islam, \{Md Maynul\} and Mufti Mahmud and \{Shamim Kaiser\}, M.",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.",

year = "2021",

doi = "10.1007/978-981-15-7561-7\_7",

language = "English",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "99--110",

booktitle = "Lecture Notes in Networks and Systems",

address = "Germany",

}

Shamma, ZS, Rumman, IJ, Raji Saikot, AM, Salim Reza, SM, Islam, MM, Mahmud, M & Shamim Kaiser, M 2021, Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease. in Lecture Notes in Networks and Systems. Lecture Notes in Networks and Systems, vol. 148, Springer Science and Business Media Deutschland GmbH, pp. 99-110. https://doi.org/10.1007/978-981-15-7561-7_7

Kidney Care: Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease. / Shamma, Zarin Subah; Rumman, Israt Jahan; Raji Saikot, Ali Mual et al.
Lecture Notes in Networks and Systems. Springer Science and Business Media Deutschland GmbH, 2021. p. 99-110 (Lecture Notes in Networks and Systems; Vol. 148).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Kidney Care

T2 - Artificial Intelligence-Based Mobile Application for Diagnosing Kidney Disease

AU - Shamma, Zarin Subah

AU - Rumman, Israt Jahan

AU - Raji Saikot, Ali Mual

AU - Salim Reza, S. M.

AU - Islam, Md Maynul

AU - Mahmud, Mufti

AU - Shamim Kaiser, M.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Fuzzy analytical hierarchy process

KW - Kidney disease

KW - Mobile App

KW - Multicriteria decision making

UR - https://www.scopus.com/pages/publications/85094945736

U2 - 10.1007/978-981-15-7561-7_7

DO - 10.1007/978-981-15-7561-7_7

M3 - Chapter

AN - SCOPUS:85094945736

T3 - Lecture Notes in Networks and Systems

SP - 99

EP - 110

BT - Lecture Notes in Networks and Systems

PB - Springer Science and Business Media Deutschland GmbH

ER -

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

Abstract

Publication series

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this