‘Virtual Operative Assistant’- Artificial Intelligence tool for simulation-based training in surgery and medicine

Simulation-based training is increasingly being used for assessment and training of psychomotor skills involved in medicine.

The application of artificial intelligence and machine learning technologies has provided new methodologies to utilize large amounts of data for educational purposes.

Virtual Operative Assistant is an platform which exploits machine learning to create automated and individualized feedback for simulation-based training in medicine and surgery.

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Advances in technology have allowed digital platforms to become integrated into educational programs. The use of these technologies allows automation of traditional forms of teaching while also re-defining valued educational goals.[1] Digital technologies can quantitate skill performance, which, when analysed with artificial intelligence can result in new perspectives on psychomotor expertise and its composites. This is particularly useful for understanding complex tasks that need to be deconstructed into small components to provide an appropriate scaffold for learning. While artificial intelligence methodologies have been employed to assess skill level on simulated tasks, efforts are needed to enhance the understanding of the classification mechanisms utilized.

The application of artificial intelligence (AI) and machine learning in various fields has substantially facilitated the evaluation of large and multivariate datasets.Several types of algorithms fit under the umbrella of machine learning. Recent literature and newer applications of AI are also focused on artificial neural networks and deep learning, subsets of AI inspired by the biological neural system. Although these models have shown significant potential in economics, finance, and medical applications, a common criticism of deep learning is that its decision-making process is a “black box”.Basically, this means that it is difficult to understand how an algorithm makes a particular decision. This is problematic in the context of education because transparency and trust are vital components of ensuring a successful connection between teacher and learner.[8] Transparency is also important for developing and implementing appropriate grading schemes and feedback mechanisms. Without such mechanisms, students report negative emotions, such as frustration and discomfort, when using technology for higher (post-secondary) education.The development of a feedback system powered by AI, and based on transparency, addresses some of these issues.

The employment of AI methodology for identifying components of expertise lends itself well for the understanding and teaching of complex tasks.[8] Virtual reality surgical simulators generate large amounts of data from each individual’s specific operative performance. This data can be analyzed and distilled to quantitate performance and provide automated feedback to the operator. This not only provides an efficient way to understand expertise, but it can also uncover unique features of skill that may have gone previously unrecognized.