Predictive Models for Post-Operative Life Expectancy after Thoracic Surgery

Anatoli Nachev, T Reapy


This paper studies data mining techniques used in medical diagnosis, particularly for predicting chance of survival of a patient after undergoing thoracic surgery. We discuss models built using decision trees, naive Bayes and support vector machines and explore suitability of each of the algorithms to perform on such data.


data mining applications; support vector machines; decision trees; naive Bayes; thoracic surgery

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