Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying

Modern machine learning algorithms aid in interpreting complex surgical motion data, even when standard analysis fails, and phase detection showed the best results with a multi-class decision jungle, but improved to 43% average accuracy with two-class boosted decision trees after Dynamic time warping (DTW) application.