Applying Case Based Reasoning System in the Treatment Decision of Gynecological Disorders: Fibroid

Abstract

Uterine fibroids are benign growths in the uterus, for which there are several possible treatment options. Patients and physicians generally approach the decision process based on a combination of the patient’s degree of discomfort, patient preferences, and physician practice patterns. A Physician’s decision-making skills are directly related to the patient’s positive outcomes. Therefore, a wealth of medical knowledge and clinical experience are key assets for a physician to have. The goal here is to use historical clinical data and relationships processed by Artificial Intelligence (AI) techniques to aid physicians in their decision making process. The System provides a large number of medical support functions to help clinician choose the best treatment measures. This paper presents case based approach to fibroid treatment decision. Both inductive indexing and nearest neighbor technique are involved in case retrieval phase. In this paper, Local similarity measure is applied to find the similarity between features while global similarity measure is applied to find the most similar case.