Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis.
Wilson OngLei ZhuWenqiao ZhangTricia KuahDesmond Shi Wei LimXi Zhen LowYee Liang ThianEe Chin TeoJiong Hao TanNaresh KumarBalamurugan A VellayappanBeng Chin OoiSwee Tian QuekAndrew MakmurJames Thomas Patrick Decourcy HallinanPublished in: Cancers (2022)
Spinal 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.
Keyphrases
- artificial intelligence
- machine learning
- clinical practice
- deep learning
- big data
- spinal cord
- high resolution
- palliative care
- randomized controlled trial
- type diabetes
- human health
- systematic review
- spinal cord injury
- prostate cancer
- skeletal muscle
- climate change
- robot assisted
- risk assessment
- loop mediated isothermal amplification
- adverse drug
- metabolic syndrome
- combination therapy
- smoking cessation