Original Article
Machine Learning Based Prediction of Non-communicable Diseases to Improving Intervention Program in Bangladesh
Author(s):
Min Hu*, Yasunobu Nohara, Yoshifumi Wakata, Ashir Ahmed, Naoki Nakashima and Masafumi Nakamura
Background: The prevalence of noncommunicable diseases (NCDs) is increasing throughout the world, including in developing countries. An NCD prevention program using information communication technology was implemented for 2 years in Bangladesh. Health checkup data were collected from 16,741 study subjects. However, the effectiveness of the utilized prevention strategy has not yet been evaluated, and some subjects with a risk of NCD have gone undetected.
Objective: This study aimed to improve intervention strategies by analyzing collected data and proposing a costeffective personalized predictive model to identify subjects predicted to be at future risk of NCD. Methods: We selected 2,110 subjects who participated in both years of the program and used a machine learning algorithm, gradien.. Read More»
DOI: 10.24105/ejbi.2018.14.4.5