Towards Designing a Medication Assistive Intelligent System with Automated Insulin-dose Prediction for Elderlies

Medication management poses significant challenges for many patients, particularly the elderlies, who often struggle with keeping track of their medication schedules and taking the correct dosages. To address this issue, this study aims to design an AI-integrated Medication Management and Assistive Unit (AMMAU) for elderlies with some important features like, schedule reminder, medicine recognition and count, early indication of shortage, sorted slots, and so on. Automated insulin-dose prediction and alert system makes the system unique and more demanding at these current scenarios. For this study, a suitable machine learning model is designed, analyzed, verified, and embedded in the proposed system so that the elderly diabetic patients can get alert, further compare with the current insulin-doses. Though, the proposed system is currently focusing on only the Basal insulin doses prediction, the system will definitely reduce the risks associated with wrong management of medication by degrading the chances of missed doses or taking wrong pills for elderlies at home.

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Publication Details

Published
2025-02-13
DOI
https://doi.org/10.1109/ecce64574.2025.11012957
Citations
1
Primary Topic
Medication Adherence and Compliance
Type
article
Field-Weighted Citation Impact
1.52
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article

Towards Designing a Medication Assistive Intelligent System with Automated Insulin-dose Prediction for Elderlies

Md. Akhtaruzzaman, Md Shofiqul Islam, Fahim Shahryer, Muhammad Towfiqur Rahman et al.
1 citations
Medication Adherence and Compliance
1.52
article

Towards Designing a Medication Assistive Intelligent System with Automated Insulin-dose Prediction for Elderlies

Md. Akhtaruzzaman, Md Shofiqul Islam, Fahim Shahryer, Muhammad Towfiqur Rahman, Jamal Uddin Tanvin, Abrar Ahmed, Minhazul Islam Mahi, Sachitra Halder
article en
1 citations

Abstract

Medication management poses significant challenges for many patients, particularly the elderlies, who often struggle with keeping track of their medication schedules and taking the correct dosages. To address this issue, this study aims to design an AI-integrated Medication Management and Assistive Unit (AMMAU) for elderlies with some important features like, schedule reminder, medicine recognition and count, early indication of shortage, sorted slots, and so on. Automated insulin-dose prediction and alert system makes the system unique and more demanding at these current scenarios. For this study, a suitable machine learning model is designed, analyzed, verified, and embedded in the proposed system so that the elderly diabetic patients can get alert, further compare with the current insulin-doses. Though, the proposed system is currently focusing on only the Basal insulin doses prediction, the system will definitely reduce the risks associated with wrong management of medication by degrading the chances of missed doses or taking wrong pills for elderlies at home.

Deakin University (AU), Intelligent Systems Research (United States) (US), University of Asia Pacific (BD), Dhaka University of Engineering & Technology (BD)
Zero hunger
Openalex Percentile: Top 16%
Medication Adherence and Compliance
1.52
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