This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively\nreflect laparoscopic surgical skill levels using an artificial intelligence system consisting of a three-layer chaos neural network. Sixtyseven\nsurgeons (23 experts and 44 novices) performed a laparoscopic skill assessment task while their hand motions were recorded\nusing a magnetic tracking sensor. Eight parameters evaluated as measures of skill in a previous study were used as inputs to the\nneural network. Optimization of the neural network was achieved after seven trials with a training dataset of 38 surgeons, with\na correct judgment ratio of 0.99. The neural network that prospectively worked with the remaining 29 surgeons had a correct\njudgment rate of 79% for distinguishing between expert and novice surgeons. In conclusion, our artificial intelligence system\ndistinguished between expert and novice surgeons among surgeons with unknown skill levels.
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