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.

Background: Addiction disorders pose significant challenges to public health, necessitating innovative treatments. This assesses deep brain stimulation (DBS) as a potential intervention for addiction disorders. Methods: A literature review was carried out with a focus on the role of DBS in addiction disorders and its future implications in neurosurgical research. Results: The online literature shows that DBS precisely modulates certain brain regions to restore addiction-related neural circuits and promote behavioral control. Conclusion: Preclinical evidence demonstrates DBS’s potential to rebalance neural circuits associated with addiction, and early clinical trials provide encouraging outcomes in enhancing addiction-related outcomes. Ethical considerations, long-term safety, and personalized patient selection require further investigation.