FUTA JOURNAL OF RESEARCH IN SCIENCE

VOLUME 13 NUMBER 2 2017

Paper Details

  • Title :FUZZY MODEL FOR OSTEOMYELITIS SEVERITY PREDICTION
  • Author(s) : Kemi Victoria Olatunde
  • Abstract:

Osteomyelitis (OM) is an infection and inflammation of the bone and bone marrow that poses serious health challenges if not diagnosed on time. It usually starts as an acute infection which if not diagnosed and treated on time can become chronic osteomyelitis, as the bones can become permanently damaged, resulting in persistent pain and loss of function. In this research, a fuzzy model for osteomyelitis severity level prediction has been proposed to aid in effective diagnosis and treatment options. The fuzzy based model was designed with six input variables and one output variable. The input variables are Fever, Redness (in the affected area), Irritability, Drainage (from the area) Swelling (in the affected area) and Stiffness (inability to use the affected area. The output variable (OsteomyelitisLevel) detects the severity levels of patients categorized into veryMild, mild, moderate, severe and verySevere. Fuzzy Inference Structure (FIS) was generated and used in obtaining a decision fuzzy set for the considered disease, and crisp decision values are obtained to state the severity level of the disease. The performance of the system was evaluated using patients’ dataset from an orthopedic department and it shows that result corresponds with the physicians evaluation.
Keywords— Osteomyelitis, Fuzzy System, Fuzzification, Membership Function, Fuzzy Rule Base.