Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning

Adel Omar; Ghassan Beydoun; Khin Win; Nagesh Shukla; Herbert F. Jelinek; Hector Elias

Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning

Adel Omar
, Ghassan Beydoun
, Khin Win
, Nagesh Shukla
, Herbert F. Jelinek
, Hector Elias

Medical Sciences

University of Technology Sydney
University of Wollongong
Griffith University

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

Abstract

Type 2 diabetes is a chronic disease that is caused by a combination of genetic and environmental factors, with social determinants playing a significant role. These social determinants include but not limited to factors such as education level, occupation, family history, ethnicity and place of residence etc. The prevalence of Type 2 diabetes (T2D) necessitates inventive management strategies. This study explores the potential of utilizing Ripple Down Rules (RDR) in comparison with Machine Learning (ML) approaches for the incremental development of a Knowledge-Based System (KBS). The aim is to create a robust Decision Support System (DSS) for effective T2D management, focusing on the dynamic influence of evolving social determinants. The research outcomes substantiate the viability of this approach. The KBS, fortified by RDRs, demonstrated notable performance metrics. Specifically, the system achieved an impressive accuracy rate of 90.2%, accompanied by a specificity of 96.9%. The sensitivity, crucial for identifying potential T2D cases, reached 73.6%, indicating the system's proficiency in recognizing diverse instances.

Original language	British English
Title of host publication	International Conference on Information Systems, ICIS 2023
Subtitle of host publication	"Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"
ISBN (Electronic)	9781713893622
State	Published - 2023
Event	44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023 - Hyderibad, India Duration: 10 Dec 2023 → 13 Dec 2023

Publication series

Name	International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"

Conference

Conference	44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023
Country/Territory	India
City	Hyderibad
Period	10/12/23 → 13/12/23

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Decision Support Systems (DSS)
Knowledge-Based Systems (KBS)
Machine Language (ML)
Ripple Down Rules (RDR)
Social Determinants
Type 2 Diabetes (T2D

OpenUrl availability

Full text

Cite this

Omar, A., Beydoun, G., Win, K., Shukla, N., Jelinek, H. F., & Elias, H. (2023). Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning. In International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies" (International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies").

Omar, Adel ; Beydoun, Ghassan ; Win, Khin et al. / Cultivating Expertise : Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning. International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies". 2023. (International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies").

@inproceedings{06e260b88ab642b4865f95ef57448f44,

title = "Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning",

abstract = "Type 2 diabetes is a chronic disease that is caused by a combination of genetic and environmental factors, with social determinants playing a significant role. These social determinants include but not limited to factors such as education level, occupation, family history, ethnicity and place of residence etc. The prevalence of Type 2 diabetes (T2D) necessitates inventive management strategies. This study explores the potential of utilizing Ripple Down Rules (RDR) in comparison with Machine Learning (ML) approaches for the incremental development of a Knowledge-Based System (KBS). The aim is to create a robust Decision Support System (DSS) for effective T2D management, focusing on the dynamic influence of evolving social determinants. The research outcomes substantiate the viability of this approach. The KBS, fortified by RDRs, demonstrated notable performance metrics. Specifically, the system achieved an impressive accuracy rate of 90.2\%, accompanied by a specificity of 96.9\%. The sensitivity, crucial for identifying potential T2D cases, reached 73.6\%, indicating the system's proficiency in recognizing diverse instances.",

keywords = "Decision Support Systems (DSS), Knowledge-Based Systems (KBS), Machine Language (ML), Ripple Down Rules (RDR), Social Determinants, Type 2 Diabetes (T2D",

author = "Adel Omar and Ghassan Beydoun and Khin Win and Nagesh Shukla and Jelinek, \{Herbert F.\} and Hector Elias",

note = "Publisher Copyright: Copyright {\textcopyright} 2023 Omar, Beydoun, Win, Shukla, Jelinek and Elias.; 44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023 ; Conference date: 10-12-2023 Through 13-12-2023",

year = "2023",

language = "British English",

series = "International Conference on Information Systems, ICIS 2023: {"}Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies{"}",

booktitle = "International Conference on Information Systems, ICIS 2023",

}

Omar, A, Beydoun, G, Win, K, Shukla, N, Jelinek, HF & Elias, H 2023, Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning. in International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies". International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies", 44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023, Hyderibad, India, 10/12/23.

Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning. / Omar, Adel; Beydoun, Ghassan; Win, Khin et al.
International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies". 2023. (International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies").

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

TY - GEN

T1 - Cultivating Expertise

T2 - 44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

AU - Omar, Adel

AU - Beydoun, Ghassan

AU - Win, Khin

AU - Shukla, Nagesh

AU - Jelinek, Herbert F.

AU - Elias, Hector

PY - 2023

Y1 - 2023

N2 - Type 2 diabetes is a chronic disease that is caused by a combination of genetic and environmental factors, with social determinants playing a significant role. These social determinants include but not limited to factors such as education level, occupation, family history, ethnicity and place of residence etc. The prevalence of Type 2 diabetes (T2D) necessitates inventive management strategies. This study explores the potential of utilizing Ripple Down Rules (RDR) in comparison with Machine Learning (ML) approaches for the incremental development of a Knowledge-Based System (KBS). The aim is to create a robust Decision Support System (DSS) for effective T2D management, focusing on the dynamic influence of evolving social determinants. The research outcomes substantiate the viability of this approach. The KBS, fortified by RDRs, demonstrated notable performance metrics. Specifically, the system achieved an impressive accuracy rate of 90.2%, accompanied by a specificity of 96.9%. The sensitivity, crucial for identifying potential T2D cases, reached 73.6%, indicating the system's proficiency in recognizing diverse instances.

AB - Type 2 diabetes is a chronic disease that is caused by a combination of genetic and environmental factors, with social determinants playing a significant role. These social determinants include but not limited to factors such as education level, occupation, family history, ethnicity and place of residence etc. The prevalence of Type 2 diabetes (T2D) necessitates inventive management strategies. This study explores the potential of utilizing Ripple Down Rules (RDR) in comparison with Machine Learning (ML) approaches for the incremental development of a Knowledge-Based System (KBS). The aim is to create a robust Decision Support System (DSS) for effective T2D management, focusing on the dynamic influence of evolving social determinants. The research outcomes substantiate the viability of this approach. The KBS, fortified by RDRs, demonstrated notable performance metrics. Specifically, the system achieved an impressive accuracy rate of 90.2%, accompanied by a specificity of 96.9%. The sensitivity, crucial for identifying potential T2D cases, reached 73.6%, indicating the system's proficiency in recognizing diverse instances.

KW - Decision Support Systems (DSS)

KW - Knowledge-Based Systems (KBS)

KW - Machine Language (ML)

KW - Ripple Down Rules (RDR)

KW - Social Determinants

KW - Type 2 Diabetes (T2D

UR - https://www.scopus.com/pages/publications/85192523192

M3 - Conference contribution

AN - SCOPUS:85192523192

T3 - International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"

BT - International Conference on Information Systems, ICIS 2023

Y2 - 10 December 2023 through 13 December 2023

ER -

Omar A, Beydoun G, Win K, Shukla N, Jelinek HF, Elias H. Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning. In International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies". 2023. (International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies").

Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning

Abstract

Publication series

Conference

UN SDGs

Keywords

OpenUrl availability

Other files and links

Fingerprint

Cite this