Fig. 2.

A framework for integrating artificial intelligence in virtual reality surgical simulation. The virtual reality surgical simulation section involves raw data acquisition from the simulator. Machine learning methodology is followed by performing metric extraction, normalization, and selection. The selected metrics are fed to a collection of machine learning algorithms, and an iterative process of parameter adjustment is followed to optimize classification accuracy. This step uses cross-validation techniques to assess classification accuracy. Once the optimal algorithm and parameters are identified, a single model is trained using all of the data. This model can then be used for generalizability testing on new subjects.