This study focuses on the development of an eHealth
application system using open-access datasets
from UCI Machine Learning Repository. This attempts to
predict the onset of diabetes and chronic
kidney diseases grounding from the generated predictive
models. Decision models are created using
C4.5, ID3 and CART algorithms with RapidMiner data
science platform. Models incurred the highest
assessment are the bases of the developed system
following Agile Software Development Life Cycle
Model. Easy access to healthcare workers through
teleconsultation, diabetes and chronic kidney
disease (CKD) online diagnosis, and maternal care
videos are possible with this study. Based on the
respondents’ response, the strongest point of the
system was its portability, which earned the highest
average mean among categories of system evaluation.
Thus, the system addresses the shortcomings
of healthcare in terms of distance and timeliness of
treatment fostering an equal access to healthcare.
Author
(s) Details
DR. Chona B. Sabinay
Biliran Province State University, Biliran, Philippines.
Maria Visitacion N. Gumabay
St. Paul University Philippines, Cagayan 3500, Philippines.
View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/263
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