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Artificial Intelligence for Neurosurgery: Current State and Future Directions
DC Field | Value | Language |
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dc.contributor.author | Noh, SH | - |
dc.contributor.author | Cho, PG | - |
dc.contributor.author | Kim, KN | - |
dc.contributor.author | Kim, SH | - |
dc.contributor.author | Shin, DA | - |
dc.date.accessioned | 2023-05-04T06:41:52Z | - |
dc.date.available | 2023-05-04T06:41:52Z | - |
dc.date.issued | 2023 | - |
dc.identifier.issn | 2005-3711 | - |
dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/25339 | - |
dc.description.abstract | Artificial 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.language.iso | en | - |
dc.title | Artificial Intelligence for Neurosurgery: Current State and Future Directions | - |
dc.type | Article | - |
dc.identifier.pmid | 36124365 | - |
dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009243 | - |
dc.subject.keyword | Artificial intelligence | - |
dc.subject.keyword | Big data | - |
dc.subject.keyword | Machine learning | - |
dc.subject.keyword | Robotic | - |
dc.contributor.affiliatedAuthor | Noh, SH | - |
dc.contributor.affiliatedAuthor | Cho, PG | - |
dc.contributor.affiliatedAuthor | Kim, SH | - |
dc.type.local | Journal Papers | - |
dc.identifier.doi | 10.3340/jkns.2022.0130 | - |
dc.citation.title | Journal of Korean Neurosurgical Society | - |
dc.citation.volume | 66 | - |
dc.citation.number | 2 | - |
dc.citation.date | 2023 | - |
dc.citation.startPage | 113 | - |
dc.citation.endPage | 120 | - |
dc.identifier.bibliographicCitation | Journal of Korean Neurosurgical Society, 66(2). : 113-120, 2023 | - |
dc.identifier.eissn | 1598-7876 | - |
dc.relation.journalid | J020053711 | - |
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