Design of an AI-Driven Personal Health Assistant System for Efficient Management of Chronic Diseases.: Design of an AI-Driven Personal Health Assistant System

Adeleke Raheem Ajiboye; Kareem Faysal Olatunbosun; Adekunle Olugbenga Ejidokun; Tomori Rasheed Adekola

doi:10.54117/7zs53k68

Authors

Adeleke Raheem Ajiboye Kampala International University
Kareem Faysal Olatunbosun University of Ilorin
Adekunle Olugbenga Ejidokun Kampala International University
Tomori Rasheed Adekola University of Ilorin, Ilorin, Nigeria

DOI:

https://doi.org/10.54117/7zs53k68

Keywords:

Chronic diseases, Support system, Artificial intelligence, UML, Design model

Abstract

Due to the increasing rates and the overwhelming burdens of chronic diseases, there is an urge for creating an innovation and intelligent health care support systems and management solutions. Chronic diseases, such as diabetes, hypertension, asthma, and cancer, among others, are life-threatening; therefore, they need continued monitoring and long-term care. This paper focuses on presenting an AI-driven personal health assistant design which intended to improve the efficient management of chronic diseases. The research demonstrates the application of artificial intelligence techniques in seamless health monitoring, personalized advice, and an informed decision-making for the patient and the healthcare provider. In order to gain a structured and detailed system design, we applied Unified Modelling Language (UML) diagrams which include: use-case, class, sequence, and activity modeling. These set of diagrams were used in the modeling of system requirements, architecture, and interactions. In addition, a number of consistency checks were carried out on the interrelationships of the designs. Findings from the system design reveals that they are logically consistent and that there is no ambiguity in terms of clarity of function since this act as a frame to guide the actual implementation later. The framework also helps to realize the potentials of AI-driven solutions, particularly in the areas of improving patient self-management, optimizing health care delivery, and reduction in the burdens involved in the course of managing chronic diseases.

Author Biographies

Adeleke Raheem Ajiboye, Kampala International University

Department of Computer Science, School of Mathematics and Computing, Kampala International University, Uganda
Kareem Faysal Olatunbosun, University of Ilorin

Department of Computer Science, Faculty of Communication and Information Sciences
Adekunle Olugbenga Ejidokun, Kampala International University

Department of Computer Science, School of Mathematics and Computing
Tomori Rasheed Adekola, University of Ilorin, Ilorin, Nigeria

Department of Computer Science, Faculty of Communication and Information Sciences University of Ilorin, Ilorin, Nigeria.

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