Prediction Thalassemia Based on Artificial Intelligence Techniques: A Survey

Thalassemia is a type of genetic disease that can be observed in many areas of the world. The first step is a CBC test to diagnose a person with thalassemia. In this paper, the used data mining methods to diagnose thalassemia are studied and evaluated. The effective parameters in thalassemia diagnosis are the available variables in the CBC test in people that among these parameters, RBC, HGB, MCV and HTC have a significant effect on the disease diagnosis. Based on the available values in the CBC test and using artificial intelligence algorithms, the patient with thalassemia is diagnosed. Artificial intelligence algorithms are used to analysis laboratory data properly, which leads to increase accuracy in the diseases diagnosis, which has a significant impact on the treatment process and improvement of patient health.