Abstract

This paper presents existing approaches for blood test parameters estimation. The proposed machine learning approach for estimation of diseases and preventive measures from the blood test parameters is described in this paper. The details of the interface designed for the evaluation of the proposed machine learning approach for estimation of diseases and preventive measures are presented. The results and evaluations of the proposed approach are presented. A graphical user interface is designed to evaluate the proposed approach. Anemia, Bleeding, Hyperlipidemia, Disruption of blood production, Hematological disorder, Iron poisoning, Dehydration, Infection, Vitamin deficiency, Viral disease, Diseases of the biliary tract, Heart diseases, Blood disease, Liver disease, Kidney disease, Iron deficiency, Muscle diseases, Lung disease, Overactive thyroid gland, Adult diabetes, Cancer, and Malnutrition these disease can be estimated by the proposed approach along with their preventive measures. The overall accuracy of the proposed system is 89.24%.