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We computer scientists face at least two problems in promoting the use of computerized data-base systems: 1) some important data might be missing; 2) there might be errors in the data. Both of these problems can be quite serious. If they cannot be solved, it will be quite hard to convince potential users that computerized information systems are useful.
BACKGROUND Patients undergoing laparoscopic Roux-en-Y bariatric surgery undergo screening esophagoduodenoscopy (EGD) during preoperative evaluation. The hypothesis is to examine the utility of this examination. The purpose of this study was to evaluate the prevalence of clinically significant upper gastrointestinal (UGI) tract findings at screening EGD in(More)
Two problems in the use of computerized data base systems are: (1) How can we estimate the values for missing data? (2) How can we improve data integrity, that is, reduce the number of errors in the data? The tool that we introduce to attack these problems is clustering analysis. Experimental results indicate that our method is feasible. Our algorithm(More)
BACKGROUND This study was designed to assess the prevalence of smoking at time of lung cancer diagnosis in a surgical patient cohort referred for cardiothoracic surgery. METHODS Retrospective study of lung cancer patients (n = 626) referred to three cardiothoracic surgeons at a tertiary care medical center in Southern California from January 2006 to(More)
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