Expert System Software Framework for Nutritional Analysis and Diet-Related Disease
Nigeria faces a serious health crisis with diet-related diseases, which calls for creative ways to improve nutritional results and public knowledge. In addressing the challenges, this study introduces an Expert System Software Framework for Nutritional Analysis and Diet-Related Diseases, leveraging advanced technologies to address healthcare and nutrition challenges. Developed through rigorous research, the framework offers dynamic capabilities, personalized recommendations, and a user-friendly interface. Key features include customized algorithms, blockchain authentication for security, dynamic scheduling, and robust administrative tools. It fills critical gaps by providing insights into nutritional contents and health impacts of foods, supporting informed decision-making and proactive management of diet-related disorders. The performance evaluation demonstrates a high accuracy rate of 91.7%, ensuring reliability in dietary recommendations. Future directions include integrating wearable technology and AI to provide real-time health data for personalized dietary recommendations. This framework sets a new standard in nutritional analysis and disease management, contributing to advancements in healthcare and nutrition. Its recommendations for sustained engagement, collaboration with medical professionals, and global expansion aim to improve user outcomes and quality of life beyond the Nigerian setting.
Authors
- Chijiuka Fortune Akuma
- Martin Emmanuel Teman
- Ogbonna J. Uchenna
- Etemi Joshua Garba (ORCID: https://orcid.org/0000-0001-6707-0220)
Institutions
- Funai Electric (Japan) (JP)
- Modibbo Adama University of Technology (NG)
Publication Details
- Journal
- International Journal of Development Mathematics (IJDM)
- Published
- 2024-09-09
- DOI
- https://doi.org/10.62054/ijdm/0103.17
- Primary Topic
- Data Mining Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00