Fuzzy approach to diagnosis and medication

Abstract

Treatment of a patient including diagnosis and prescription of medicines is a major challenge. Since patients travel from
place to place and face problems like availability of medicines in different locations, it becomes essential to follow the
concept of mobile treatment. In today’s world, the concept of telemedicine has evolved as a new approach. In several
situations, the doctor may not be available physically to treat the patient. It is essential to have a system that ensures that all
types of patients like child, adult or senior citizen get proper treatment. In this work, a fuzzy based model has been
designed to diagnose the sickness based on age, symptoms and lab tests. The patient’s case history is captured in a database
and is continuously updated. The data is acquired by android-based applications linked to a server. Though the patient may
be treated in different hospitals, it is possible to group the data by cloud computing. The fuzzy based technique assesses the
patient’s symptoms and decides the drug dosage based on a rule set. The higher the rule strength more effective is the
diagnosis. The fuzzy based technique reduces drug adherence by 32% and improves drug dosage by 29%, compared to the
manual technique of diagnosis.