The results of the study showed the prediction accuracies of total analgesic consumption and PCA requirement by an ensemble of decision trees were 80.9 percent and 73.1 percent, respectively.
Decision tree-based learning outperformed several other classifiers in analgesic consumption prediction. Results also demonstrated the feasibility of the proposed ensemble approach to postoperative pain management to assist anesthesiologists with PCA administration.
More Articles on Anesthesia:
Data Supports Using EXPAREL Infiltration To Control Postsurgical Pain
Dr. Terence Robertson Joins Anesthesia Staff at Bothwell Regional Health Center
Should CRNAs Treat Chronic Pain? Q&A With ASIPP Chairman Dr. Laxmaiah Manchikanti
At the Becker’s 32nd Annual Meeting: The Business and Operations of ASCs, taking place October 29-31 in Chicago, ASC leaders, surgeons and healthcare executives will explore strategies to drive growth, enhance operational performance, navigate reimbursement challenges and prepare for the future of ambulatory surgery. Apply for complimentary registration now.
