The future of artificial intelligence in neurosurgery: A narrative review

Abstract

Background: Artificial intelligence (AI) and machine learning (ML) algorithms are on the tremendous rise for being incorporated into the field of neurosurgery. AI and ML algorithms are different from other technological advances as giving the capability for the computer to learn, reason, and problem-solving skills that a human inherits. This review summarizes the current use of AI in neurosurgery, the challenges that need to be addressed, and what the future holds. Methods: A literature review was carried out with a focus on the use of AI in the field of neurosurgery and its future implication in neurosurgical research. Results: The online literature on the use of AI in the field of neurosurgery shows the diversity of topics in terms of its current and future implications. The main areas that are being studied are diagnostic, outcomes, and treatment models. Conclusion: Wonders of AI in the field of medicine and neurosurgery hold true, yet there are a lot of challenges that need to be addressed before its implications can be seen in the field of neurosurgery from patient privacy, to access to high-quality data and overreliance on surgeons on AI. The future of AI in neurosurgery is pointed toward a patient-centric approach, managing clinical tasks, and helping in diagnosing and preoperative assessment of the patients.

Recent Outcomes and Challenges of Artificial Intelligence, Machine Learning, and Deep Learning in Neurosurgery

“…Hand tremors perioperatively have been observed to increase the risk of complications both during and postoperatively, as well as collateral damage. 59 Many AI models have been incorporated into surgical education under the pretence of virtual reality (VR) and 3D simulators to provide sufficient, skill-oriented training for resident and mid-career surgeons to increase their confidence and reduce hand tremors perioperatively ( Fig. 1 ).…”

Advancements and Challenges in the Application of Artificial Intelligence in Surgical Arena: A Literature Review

“…Machine learning algorithms help in real-time tumor segmentation, aiding surgeons in the removal of brain tumors while minimizing damage to healthy tissues. Additionally, AI-powered diagnostic tools can enhance the detection of neurological disorders, such as strokes, by rapidly analyzing medical imaging data [ 19 , 20 ].…”

Accessible Spinal Surgery: Transformation Through the Implementation of Exoscopes As Substitutes for Conventional Microsurgery in Low- and Middle-Income Settings

“…Comparative assessments of video quality between EXs and traditional OMs yield varying results, with certain studies favoring EXs for superior visual quality and enhanced surgeon comfort. One area where EXs excel is in ergonomic design, contributing to reduced surgeon fatigue and optimized efficiency [ 4 , 5 ]. The availability of advanced surgical equipment is often limited in low- and middle-income settings.…”

“…Expanding the scope of investigation beyond spinal surgeries to encompass a diverse array of neurosurgical procedures is crucial to fully understand the versatility and efficacy of EX techniques. Additionally, an emphasis on patient-centric parameters, such as the duration of the surgical procedure, intraoperative blood loss, incidence of complications, management of postoperative pain, overall quality of life, and levels of patient satisfaction, will yield valuable insights into the comprehensive ramifications of EX interventions [ 3 - 5 ]. Investigating the learning curve associated with EX procedures and establishing standardized training protocols are imperative steps toward ensuring skill acquisition and proficiency among surgeons.…”