Human-Centric Intelligent Systems

Volume 1, Issue 3-4, December 2021, Pages 75 - 85

DiaVis: Exploration and Analysis of Diabetes through Visual Interactive System

Authors
Mosiur Rahman1, Md Rafiqul Islam2, *, Sharmin Akter1, Shanjita Akter3, Linta Islam4, Guandong Xu2
1Department of Computer Science & Engineering, City University, Bangladesh
2Advanced Analytics Institute (AAi), University of Technology Sydney (UTS), Australia
3Department of Computer Science & Engineering, Islamic University of Technology (IUT), Bangladesh
4Department of Computer Science & Engineering, Jagannath University, Bangladesh
*Corresponding author. Email: MdRafiqul.Islam-1@student.uts.edu.au
Corresponding Author
Md Rafiqul Islam
Received 23 August 2021, Accepted 19 October 2021, Available Online 27 November 2021.
DOI
https://doi.org/10.2991/hcis.k.211025.001How to use a DOI?
Keywords
Diabetes disease; visual analytics; visual interactive system; qualitative analysis; machine learning
Abstract

Background: Diabetes is a long-term disease characterized by high blood sugar and has risen as a public health problem globally. Exploring and analyzing diabetes data is a timely concern because it may prompt a variety of serious illnesses, including stroke, kidney failure, heart attacks, etc. Several existing pieces of research have revealed that diabetes data, such as systolic blood pressure (SBP), diastolic blood pressure (DBP), weight, height, age, etc., can provide insightful information about patients diabetes states. However, very few studies have focused on visualizing diabetes mellitus (DM) insights to support healthcare administrator (HA)’s goals adequately, such as (i) decision-making, (ii) identifying and grouping associated factors, and (iii) analyzing large data effectively remains unexplored.

Objective: This study aims to design an interactive Visualization system (Vis) to explore diabetes mellitus (DM) insights and its associated factors in Bangladesh.

Methods: In this study, first, a case study method has employed to understand diabetes data. Second, we examine the potential of user-centered technology in addressing these challenges and design a Vis named “DiaVis” to process and present raw data in the form of graphics, graphs, and processed text, as well as a variety of user interaction possibilities. It helps to extract valuable data and present it in a simple and easy-to-understand way. Moreover, we highlight some key insights from our study that may help explore the healthcare community.

Results: A user study with 20 individuals is used to evaluate our system. By allowing iterative exploration and modification of data in a dashboard with multiple-coordinated views, the DiaVis system improves the flow of visual analysis.

Conclusion: This study suggests that the healthcare community should pay more attention to developing appropriate policy measures to reduce the risk of DM.

Copyright
© 2021 The Authors. Publishing services by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Human-Centric Intelligent Systems
Volume-Issue
1 - 3-4
Pages
75 - 85
Publication Date
2021/11/27
ISSN (Online)
2667-1336
DOI
https://doi.org/10.2991/hcis.k.211025.001How to use a DOI?
Copyright
© 2021 The Authors. Publishing services by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Mosiur Rahman
AU  - Md Rafiqul Islam
AU  - Sharmin Akter
AU  - Shanjita Akter
AU  - Linta Islam
AU  - Guandong Xu
PY  - 2021
DA  - 2021/11/27
TI  - DiaVis: Exploration and Analysis of Diabetes through Visual Interactive System
JO  - Human-Centric Intelligent Systems
SP  - 75
EP  - 85
VL  - 1
IS  - 3-4
SN  - 2667-1336
UR  - https://doi.org/10.2991/hcis.k.211025.001
DO  - https://doi.org/10.2991/hcis.k.211025.001
ID  - Rahman2021
ER  -