Methadone Flexi Dispensing (MFlex) Intelligence System utilizing the Mahalanobis-Taguchi System

Pinueh, N.S. and Abu, Mohd Yazid and S K M, Saad and N.H, Aris and Sari, E. (2023) Methadone Flexi Dispensing (MFlex) Intelligence System utilizing the Mahalanobis-Taguchi System. Journal of Modern Manufacturing Systems and Technology (JMMST), 7 (1). pp. 30-41. ISSN 2636-9575. (Published)

[img]
Preview
Pdf
publication2-PGRS230321.pdf
Available under License Creative Commons Attribution.

Download (739kB) | Preview

Abstract

Patients who are participating in the methadone flexi dispensing (MFlex) program are obliged to provide their blood samples for various testing, such as lipid profiles. A doctor evaluates three parameters, including cholesterol, HDL cholesterol, and LDL cholesterol to determine whether or not the patient has a lipid issue. Since, the current structure lacks an ideal atmosphere for classification and optimization caused by inaccuracies in measurement methodologies and a lack of explanation for significant aspects that have an effect on the accuracy of diagnostics. The objective is to implement the Mahalanobis Taguchi system (MTS) in the MFlex program. Utilizing a total of 34 parameters, there are two different types of MTS techniques used for classification and optimization: the RT method and T method. The average Mahalanobis distance (MD) for healthy conditions is 1.0000 whereas for unhealthy is 79.5876. As a result, there is 19 parameters indicate a positive degree of contribution. 15 unknown samples were diagnosed with a variety of positive and negative degree of contribution to achieving a lower MD. Type 5 of 6 alterations was chosen as the best suggested possibility. In conclusion, MTS is able to be applied in medical environment.

Item Type: Article
Uncontrolled Keywords: MTSM; Flex; Classification; Optimization; Blood Tests
Subjects: T Technology > T Technology (General)
T Technology > TS Manufactures
Faculty/Division: Faculty of Manufacturing and Mechatronic Engineering Technology
Institute of Postgraduate Studies
Depositing User: Dr. Mohd Yazid Abu
Date Deposited: 27 Feb 2024 00:02
Last Modified: 27 Feb 2024 00:02
URI: http://umpir.ump.edu.my/id/eprint/40497
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item