Data Mining Approach In A Selection Of Laparoscopic Techniques

The objective of our study is to assess and formalize the decision process in selection of different insufflation methods in women undergoing laparoscopy. Data mining analysis was performed using retrospective data that are results of 13 years of experience at University of Louisville Hospital. Information about laparoscopic procedures on 3086 women were stored in the database. Five different laparoscopic techniques where evaluated: standard transumbilical insufflation, open laparoscopy, transuterine insufflation, subcostal. insufflation and direct trocar insertion technique. Using data mining approach formalized criteria, for a selection of laparoscopic techniques, are presented in a form of decision rules.