Please use this identifier to cite or link to this item: https://doi.org/10.3390/cancers14164025
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dc.titleApplication of Artificial Intelligence Methods for Imaging of Spinal Metastasis
dc.contributor.authorOng, Wilson
dc.contributor.authorZhu, Lei
dc.contributor.authorZhang, Wenqiao
dc.contributor.authorKuah, Tricia
dc.contributor.authorLim, Desmond Shi Wei
dc.contributor.authorLow, Xi Zhen
dc.contributor.authorThian, Yee Liang
dc.contributor.authorTeo, Ee Chin
dc.contributor.authorTan, Jiong Hao
dc.contributor.authorKumar, Naresh
dc.contributor.authorVellayappan, Balamurugan A
dc.contributor.authorOoi, Beng Chin
dc.contributor.authorQuek, Swee Tian
dc.contributor.authorMakmur, Andrew
dc.contributor.authorHallinan, James Thomas Patrick Decourcy
dc.date.accessioned2022-09-14T00:47:14Z
dc.date.available2022-09-14T00:47:14Z
dc.date.issued2022-08-01
dc.identifier.citationOng, Wilson, Zhu, Lei, Zhang, Wenqiao, Kuah, Tricia, Lim, Desmond Shi Wei, Low, Xi Zhen, Thian, Yee Liang, Teo, Ee Chin, Tan, Jiong Hao, Kumar, Naresh, Vellayappan, Balamurugan A, Ooi, Beng Chin, Quek, Swee Tian, Makmur, Andrew, Hallinan, James Thomas Patrick Decourcy (2022-08-01). Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis. CANCERS 14 (16). ScholarBank@NUS Repository. https://doi.org/10.3390/cancers14164025
dc.identifier.issn20726694
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/231089
dc.description.abstractSpinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.
dc.language.isoen
dc.publisherMDPI
dc.sourceElements
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectOncology
dc.subjectartificial intelligence
dc.subjectmachine learning
dc.subjectdeep learning
dc.subjectspinal metastasis
dc.subjectimaging
dc.subjectapplications
dc.subjectAPPARENT DIFFUSION-COEFFICIENT
dc.subjectSTEREOTACTIC BODY RADIOTHERAPY
dc.subjectPROMOTER METHYLATION STATUS
dc.subjectBONE METASTASES
dc.subjectCORD COMPRESSION
dc.subjectPREOPERATIVE EVALUATION
dc.subjectTHORACOLUMBAR SPINE
dc.subjectCLINICAL-FEATURES
dc.subjectCANCER PATIENTS
dc.subjectSCORING SYSTEM
dc.typeReview
dc.date.updated2022-09-13T23:56:35Z
dc.contributor.departmentCHEMISTRY
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.contributor.departmentDIAGNOSTIC RADIOLOGY
dc.contributor.departmentMEDICINE
dc.description.doi10.3390/cancers14164025
dc.description.sourcetitleCANCERS
dc.description.volume14
dc.description.issue16
dc.published.statePublished
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