Sadaf Qazi1, Muhammad Usman1, Azhar Mahmood1, Aaqif Afzaal Abbasi2, Muhammad Attique3, Yunyoung Nam4,*
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 589-602, 2021, DOI:10.32604/cmc.2020.012507
- 30 October 2020
Abstract Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases, child mortality and morbidity. Expanded Program
on Immunization (EPI) is a nation-wide program in Pakistan to implement immunization activities, however the coverage is quite low despite the accessibility of
free vaccination. This study proposes a defaulter prediction model for accurate
identification of defaulters. Our proposed framework classifies defaulters at five
different stages: defaulter, partially high, partially medium, partially low, and
unvaccinated to reinforce targeted interventions by accurately predicting children
at high risk of defaulting from the immunization schedule. Different machine
learning algorithms are… More >
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