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Original Article
Developing a predictive intelligent model for early detection of Non-Communicable Diseases: Case study Kitui County
Nicole Chepngetich1
David Muriuki2
Mwirigi Kiula3
1 2 Department of Computer Science and Information Technology, Co-operative University of Kenya, Kenya. 3 Department of Mathematical Sciences, Co-operative University of Kenya, Nairobi, Kenya.
Published Online: September-December 2025
Pages: 105-110
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250403020
References
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pp. 45–56, 2021.
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2023.
Data Mining, 2016, pp. 785–794, doi: 10.1145/2939672.2939785.
2. P. M. Gichuhi, C. M. Ndungu, and J. Kariuki, “Barriers to early detection of chronic diseases in Kenya,” Afr. J. Health Sci., vol. 34, no. 2,
pp. 45–56, 2021.
3. S. Mabaso, E. Tambo, and M. Mutuku, “Leveraging predictive analytics in African healthcare systems,” BMC Public Health, vol. 23, no. 12,
p. 550–562, 2023, doi: 10.1186/s12889-023-1550-2.
4. Ministry of Health (MOH), Kenya Health Sector Strategic Plan 2023–2028. Nairobi, Kenya: Government of Kenya, 2023.
5. J. Nkengasong, “Predictive health models in Sub-Saharan Africa,” Science, vol. 369, no. 6504, pp. 627–630, 2020, doi:
10.1126/science.369.6504.627.
6. Z. Obermeyer, B. Powers, C. Vogeli, and S. Mullainathan, “Dissecting racial bias in algorithmic predictions,” Science, vol. 366, no. 6464,
pp. 447–453, 2019, doi: 10.1126/science.aax2342.
7. M. K. Onyango, J. N. Mwangi, and P. Oduor, “Challenges in implementing predictive modeling in low-resource settings,” Kenya Med. Res.
J., vol. 12, no. 3, pp. 250–268, 2020.
8. W. Raghupathi and V. Raghupathi, “Machine learning in chronic disease management: Opportunities and challenges,” Health Policy
Technol., vol. 10, no. 2, pp. 129–141, 2021, doi: 10.1016/j.hlpt.2021.02.004.
9. X. Wang, Y. Li, and L. Zhou, “Predictive modeling for NCD detection using ensemble learning,” J. Epidemiol., vol. 15, no. 1, pp. 75–89,
2023.
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