Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study.

The tested algorithms provide an automated way to filter intraoperative temperature artifacts that closely approximates manual sorting by anesthesiologists. Our study provides evidence demonstrating the efficacy of highly generalizable artifact reduction algorithms that can be readily used by observational studies that rely on automated intraoperative data acquisition.