Discovering comprehensible classification rules using Genetic Programming: a case study in a medical domain
Celia C. Bojarczuk, Av. Sete De Setembro, Heitor S. Lopes, Alex A. Freitas, Rua Imaculada Conceio · 1999
This work it is intended to discover classification rules for diagnosing certain pathologies. These rules are capable of discriminating among 12 different pathologies, whose main symptom is chest pain. In order to discover these rules it was used genetic programming as well as some concepts of data mining, particularly the emphasis on the discovery of comprehensible knowledge. 1 INTRODUCTION In order to classify and diagnose some pathology, one must verify which predicting attributes are most associated with that disease. In this work there are 189 predicting attributes and 12 different diseases (classes) whose main characteristic is chest pain. The predicting attributes refer to characteristics of the chest pain, other symptons reported by the patient, signals observed by the physician, details of clinical history and results of laboratory tests. The diseases are: stable angina, unstable angina, acute myocardial infarction, aortic dissection, cardiac tamponade, pulmonary emb...