Improve the Accuracy and Efficiency of Medical Diagnosis Analysis Using Knowledge Discovery

Abstract

The main objective Computer-based support in health care is becoming ever more important. No other domain has so many innovative changes that have such a high social impact. There has already been a long standing tradition for computer-based decision support, dealing with complex problems in medicine such as diagnosing disease, managerial decisions and assisting in the prescription of appropriate treatment. The Healthcare industry is among the most information intensive industries. Medical information, knowledge and data keep growing on a daily basis. It has been estimated that an acute care hospital may generate five terabytes of data a year. The ability to use these data to extract useful information for quality healthcare is crucial. Computer assisted information retrieval may help support quality decision making and to avoid human error. Although human decision-making is often optimal, it is poor when there are huge amounts of data to be classified. Also efficiency and accuracy of decisions will decrease when humans are put into stress and immense work. Imagine a doctor who has to examine 5 patient records; he or she will go through them with ease. But if the number of records increases from 5 to 50 with a time constraint, it is almost certain that the accuracy with which the doctor delivers the decisions will not be as high as the ones obtained when he had only five records to be analyzed.