The classification of patient blood samples with machine learning techniques

Abstract

After implementing the Jaminan Kesehatan Nasional (JKN) in Indonesia, health system inequity, payment non-compliance and additional expenditure still exists. To better deal with the problems in their healthcare system, this study uses a variety of machine learning algorithms to classify patient blood samples for improving the efficiency of healthcare system. The study shows that most of the algorithms are up to 70% accuracy and the accuracy will rise with only important variables.