An intelligent decision support system based on fuzzy techniques and neural networks for purchasing medical supplies

The supply chains of medical equipment and necessities in healthcare centers are highly complex, diverse, and dynamic, making optimal selection and purchase a specialized and challenging task. This research aimed to design an intelligent decision support system that could aid the expertise process of purchasing medical supplies.

In this developmental-applied and descriptive-survey study, we used artificial intelligence, fuzzy sets, and neural networks as well as MATLAB software to design a model that could simulate the decision-making process of experts in the purchase of medical supplies by predicting the score of medical supplies after obtaining information. The required data was extracted from the website of the General Directorate of Medical Equipment and Knowledge of Specialists in 2022.

The results showed that a three-layer perceptron neural network, with a mean square error of 0.0011 and an overall correlation of 0.97, could be used as a suitable decision aid in the evaluation and selection of medical supplies.

The use of an intelligent decision support system can greatly aid the expertise process of purchasing medical supplies, thus helping the healthcare system to preserve resources and improve the quality of healthcare services. The high speed and accuracy of processing data by using neural networks, one of the most effective methods for learning and generalizing, can assist experts in purchasing medical supplies and lead to optimal decision-making.