A framework for diagnosing confusable diseases using neutrosophic based neural network

Abstract

The two major motivations in medical science are to prevent and diagnose diseases. Diagnosis of disease must be done with care since it is the first stage of therapeutic actions towards eventual management of the disease; a mistake at this stage is disastrous and such adequate care must be ensured. Diagnosis becomes difficult in medical domain due to influence of medical uncertainties that arises from confusability in disease symptomatic presentation between two diseases. This confusability of these diseases stems from the overlaps in the disease symptomatic presentation and has led to misdiagnosis with various degrees of associated costs and in worst cases led to death. In this research, we present the analysis of the existing systems and finally present a framework for the diagnosis of confusable disease using neutrosophic-based neural network.

General Terms: Clinical Decision Support System, Medical Diagnosis, Machine Learning, Soft Computing.

Keywords: Decision Support System, Medical Uncertainties, Neutrosophic Logic, Confusable Diseases