Pancreatic islet transplantation consists of replacing insulin-producing cells to restore normal glycemia in diabetic patients. This is a minimal invasive procedure that has been proved successful. Unfortunately unpredictability of islet transplant outcome remains a frustrating and costly issue limiting the clinical implementation of this procedure. Multiple variables are involved in the procedure and assessment is subjective to individual operators. The aim of this study was to generate a system expressing the probability of transplant success in relation to four classes of identified variables (donor, organ, isolation and recipient). We have proposed the utilization of Multi-Criteria Decision Making methods (MCDM) as a powerful tool for evaluating pancreatic islet transplant-related information with the goal to achieve optimal decision. Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS), one of the most widely used MCDM methods in decision support systems, was here utilized with modification to fit better in a medical system. In our modified method, we have utilized fuzzy logic in order to consider uncertain and vague data.
- Decision making
- Fuzzy TOPSIS
- Pancreatic islets transplantation
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence