Artificial Intelligence in Neurosurgery: Pre, Intra and Post Operation Applications

Abstract

Background: Artificial intelligence (AI) and Machine Learning (ML) have recently forayed into human healthcare.There is a growing interaction of AI in several neurological and neurosurgical practices.The main goals of this study are to ascertain the different uses of AI in the elaborate field of Neurosurgery and elucidate its uses.Additionally the study also quantify the existing use of AI assisted robotic neurosurgery. Materials and Methods:A literature review using keywords 'Artificial Intelligence' and 'Neurosurgery' was conducted.Data charting was done using a structured format as per the Joanna Briggs Institute (JBI) methodology for scoping reviews.The articles retrieved were segregated into various subheadings (pre, intra and post-operative) and a review based on each topic was conducted.Results & Discussions: AI has the potential to expand surgeons' skill sets during pre-, intra-, and postoperative neurosurgery.AI has proved to be essential in the generation, processing, and storage of clinical and experimental data.Additionally, neurosurgery and AI can form a symbiotic connection in which neurosurgery helps AI push the frontiers of the field and AI helps neurosurgery to create more reliable and superior algorithms.Conclusions: AI can reduce the healthcare costs and errors or delays in medical management.By enhancing diagnostic and prognostic outcomes in clinical treatment and assisting neurosurgeons with decision-making during surgical interventions to improve patient outcomes, AI complements neurosurgeons' skills in providing patients with the best interventional and noninterventional care possible.Further research, financing, and multidisciplinary collaboration is required for wider societal impact.

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