A Medical Expert System for Predicting the Prevalence of Autoimmune Diabetes Mellitus in Thyroid Patients

Surekha Samsani *, srinivasa rao**
* Department of Computer Science and Engineering, UCEK(A), Jawaharlal Nehru Technological University Kakinada, Andhra Pradesh, India.
** Department of Information Technology, UCEV(A), Jawaharlal Nehru Technological University Kakinada, Andra Pradesh, India.
Periodicity:December - February'2019
DOI : https://doi.org/10.26634/jpr.5.4.15947

Abstract

Diabetes Mellitus (DM) and Thyroid are the major coexistent autoimmune disorders affecting people globally. Due to prolonged chronic mental stress in the modern lifestyle, Thyroid disorder is affecting all age groups and people with Thyroid disorder have an increased risk of developing DM complications. Because, abnormal Thyroid dysfunction can have dreadful effects on blood glucose control and can affect the course of DM. This paper proposes a Medical Expert system to assist clinicians in predicting the prevalence of developing autoimmune DM more precisely in patients suffering from Thyroid and further helps to investigate better in the line of improving public health. In this work, Fuzzy logic based inference system and unsupervised machine learning algorithms are used to discover associations and dependencies between Thyroid and DM. The inferred knowledge base is used to design Fuzzy based Expert system. To develop a more realistic expert system, blood sample reports of people affected by DM and Thyroid disorder have been collected from various Endocrine centres in Andhra Pradesh, India. Specificity, Sensitivity, Predictive Values, and Likelihood Ratios of the proposed system are promising in support of system functionality

Keywords

Medical Expert System, Diabetes Mellitus, Thyroid Disorder, Fuzzy Logic, Machine Learning.

How to Cite this Article?

Samsani,S.,&Suma,G.J. (2019). A Medical Expert System for Predicting the Prevalence of Autoimmune Diabetes Mellitus in Thyroid Patients. i-manager’s Journal on Pattern Recognition, 5(4), 44-50. https://doi.org/10.26634/jpr.5.4.15947

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