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      The future of artificial intelligence in neurosurgery: A narrative review

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

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          Most cited references57

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          Machine Learning in Medicine.

          Rahul Deo (2015)
          Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games - tasks that would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in health care. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades, and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus, part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome.
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            Artificial Intelligence in Surgery

            The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments.
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              Privacy in the age of medical big data

              Big data has become the ubiquitous watch word of medical innovation. The rapid development of machine-learning techniques and artificial intelligence in particular has promised to revolutionize medical practice from the allocation of resources to the diagnosis of complex diseases. But with big data comes big risks and challenges, among them significant questions about patient privacy. Here, we outline the legal and ethical challenges big data brings to patient privacy. We discuss, among other topics, how best to conceive of health privacy; the importance of equity, consent, and patient governance in data collection; discrimination in data uses; and how to handle data breaches. We close by sketching possible ways forward for the regulatory system.
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                Author and article information

                Contributors
                https://orcid.org/0000-0003-3383-9884
                https://orcid.org/0000-0001-7943-7106
                https://orcid.org/0000-0001-8972-5435
                https://orcid.org/0000-0003-3863-5872
                https://orcid.org/0000-0002-3553-0402
                Journal
                Surg Neurol Int
                Surg Neurol Int
                Surgical Neurology International
                Scientific Scholar (USA )
                2229-5097
                2152-7806
                2022
                18 November 2022
                : 13
                : 536
                Affiliations
                [1 ]School of Medicine, King Edward Medical University Lahore, Punjab, Pakistan,
                [2 ]School of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan,
                [3 ]Department of Internal Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan,
                [4 ]School of Medicine, Government Medical College, Siddipet, Telangana, India,
                [5 ]Department of Community Medicine, Fatima Jinnah Medical University, Lahore, Punjab, Pakistan,
                [6 ]Wolfson School of Medicine, University of Glasgow, Scotland, United Kingdom,
                [7 ]House Officer, Holy Family Hospital Rawalpindi, Punjab, Pakistan,
                [8 ]School of Medicine, Sharif Medical City Hospital, Lahore, Punjab, Pakistan.
                Author notes
                [* ] Corresponding author: Javed Iqbal, School of Medicine, King Edward Medical University, Lahore, Punjab, Pakistan. ijaved578578@ 123456gmail.com
                Article
                10.25259/SNI_877_2022
                10.25259/SNI_877_2022
                9699882
                36447868
                59f2ec93-cf28-4571-9bf3-3aa917d3d482
                Copyright: © 2022 Surgical Neurology International

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

                History
                : 21 September 2022
                : 27 October 2022
                Categories
                Review Article

                Surgery
                artificial intelligence,health care,machine learning,neurosurgery,operating room,technology
                Surgery
                artificial intelligence, health care, machine learning, neurosurgery, operating room, technology

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