Extracting Information from Medical Reports

Abstract

This paper aims to present an Information Extraction (IE) system for extracting knowledge from medical records. The process of extracting data from unstructured text sources is known as information extraction. Medical records were gathered from Gaza hospitals that written in both Arabic and English languages. Then, a model was defined for converting unstructured medical text into structured form. Furthermore, association rules were used to create useful rules from structured data. These rules can be used to assist medical personnel in detecting hidden relationships in medical data and making decisions that can enhance patient care. The paper proposed two approaches to assess our work: objective and subjective. For the objective assessment of association rules, support and confidence measures were used. A questionnaire was used to evaluate the produced rules by medical experts for subjective evaluation. The produced rules were found to be useful by 87% of the medical experts.