Estimating the Approximate Necessity of Essential Medicines in Syria Using Machine Learning

Abstract

Essential Medicines are one of the very crucial parts of the health care needs. This article focuses on the estimation of the approximate necessity of essential medicines in the Syrian Arab Republic. Since 1977, when the idea of essential drugs or medicines was introduced by the WHO, it has been playing a vital role in society's betterment. Syria is no exception in that case. Since 2011, Syria’s health care systems have been facing many problems. To make the situation better, it is necessary to focus on the modernization of the health care needs. After researching briefly about the usage, regulations, supply, and production of essential medicines in the Russian Federation, Germany, and the USA, ‌the application of artificial intelligence seems like an ultimate necessity to make health care needs seamless and rapid. In this article, a machine learning approach is applied to predict the demand for different essential medicines in different regions of Syria. The task includes research methods, implementation, results, related work, and analysis for future progression. Random Forest Classifier is used to estimate the accuracy of the approach method.