Fuzzy rule based expert system to diagnose spinal cord disorders

On time diagnosis of spinal cord problems is essential because of patient pain and cost of treatment. To alleviate this hazard, in this research a fuzzy rule-based expert system is proposed to diagnosis spinal cord problems and clarify whether a MRI scan is necessary or not. The knowledge representation of this system is provided from high level, based on lifestyle of the patient and historical data about his/her problem and some of the clinical examination. It organized to 5 sub problem, called Red flag, Spinal stenosis, Scoliosis Lordosis kyphosis, and Mechanical and Spinal disc herniation. Spinal disc herniation is composed of 2 sub problem including Lumbar and cervical. Inference engine of the system is a combination of backward and forward chaining. To reduce diagnosis time, it switches from forward to backward mode and vice versa based on direct and indirect approach. Results of this system is the degree of each problem the patient has and it reduces complexity in image processing for analysis the M.R.I of the patient.