Statistical methods for managing missing data: Application to medical diagnosis

Abstract

This paper presents a work consisting in realizing a decision support system based on the technique of case-base reasoning and dedicated to the diagnosis of a very dangerous pulmonary pathology: lung cancer. The system is realized for the oncology department of Ibn roch hospital of Annaba (Algeria) and will help young oncologist physicians in their activity by providing them with the experience of experts in the same domain. The principle issue in this work is the missing data in the system memory relating to the patient’s state. Indeed, missing values prevent the achievement of the diagnosis process. The problem is treated by proposing two statistical approaches in addition to re-evaluate in this new domain some ones which have been already proposed and evaluated in a previously domain. The validation is made on a base of 40 real cases collected from the archive of oncology department. Cases are collected as paper documents.