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Artificial Intelligence for Neurosurgery : Current State and Future Directions

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dc.contributor.author김긍년-
dc.contributor.author신동아-
dc.contributor.author노성현-
dc.date.accessioned2024-03-22T05:44:34Z-
dc.date.available2024-03-22T05:44:34Z-
dc.date.issued2023-03-
dc.identifier.issn2005-3711-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/198179-
dc.description.abstractArtificial intelligence (AI) is a field of computer science that equips machines with human-like intelligence and enables them to learn, reason, and solve problems when presented with data in various formats. Neurosurgery is often at the forefront of innovative and disruptive technologies, which have similarly altered the course of acute and chronic diseases. In diagnostic imaging, such as X-rays, computed tomography, and magnetic resonance imaging, AI is used to analyze images. The use of robots in the field of neurosurgery is also increasing. In neurointensive care units, AI is used to analyze data and provide care to critically ill patients. Moreover, AI can be used to predict a patient’s prognosis. Several AI applications have already been introduced in the field of neurosurgery, and many more are expected in the near future. Ultimately, it is our responsibility to keep pace with this evolution to provide meaningful outcomes and personalize each patient’s care. Rather than blindly relying on AI in the future, neurosurgeons should gain a thorough understanding of it and use it to enhance their patient care.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherKorean Neurosurgical Society-
dc.relation.isPartOfJOURNAL OF KOREAN NEUROSURGICAL SOCIETY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleArtificial Intelligence for Neurosurgery : Current State and Future Directions-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurosurgery (신경외과학교실)-
dc.contributor.googleauthorSung Hyun Noh-
dc.contributor.googleauthorPyung Goo Cho-
dc.contributor.googleauthorKeung Nyun Kim-
dc.contributor.googleauthorSang Hyun Kim-
dc.contributor.googleauthorDong Ah Shin-
dc.identifier.doi10.3340/jkns.2022.0130-
dc.contributor.localIdA00331-
dc.contributor.localIdA02092-
dc.relation.journalcodeJ01520-
dc.identifier.eissn1598-7876-
dc.identifier.pmid36124365-
dc.subject.keywordArtificial intelligence-
dc.subject.keywordBig data-
dc.subject.keywordMachine learning-
dc.subject.keywordRobotics-
dc.contributor.alternativeNameKim, Keung Nyun-
dc.contributor.affiliatedAuthor김긍년-
dc.contributor.affiliatedAuthor신동아-
dc.citation.volume66-
dc.citation.number2-
dc.citation.startPage113-
dc.citation.endPage120-
dc.identifier.bibliographicCitationJOURNAL OF KOREAN NEUROSURGICAL SOCIETY, Vol.66(2) : 113-120, 2023-03-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers

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