Efficient fuzzy-based system for the diagnosis and treatment of tuberculosis (efbsdttb)

The aim of this study is to design a FuzzyBased Expert System for Tuberculosis diagnosis and Treatment. The designed system made use of General Hospital Adikpo, patient database. The system has 18 input fields and five outputs field. Input fields are Chest pain (CP), cough duration (CD), fever duration (FV), night sweats (NS), weight loss (WL), loss of appetite (LOA), change in bowel habits (CBH), variations in mental behaviour (VMB), masses along the neck (MAN), draining sinus (DS), coma (seizure) (CO), stiff Neck (SN), headache (HD), abdominal Pain (AP), painful or uncomfortable urination (PU), hemopysis (coughing up blood) (CUB), fatigue (FA) and blood present in urine (BPU). The output fields refers to the class/group of tuberculosis disease in the patient. This system uses Mamdani inference method. The results obtained from designed system are compared with the data in the database and observed results of designed system are correct. The system was designed with Java (Jfuzzylogic), Microsoft visio (2013), mySql workbench, MySql database, JSP and XHML.