Abstract
Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis. While radiomics has been classically applied to tumor analysis, there is promising research in its application to spine surgery, including spinal deformity, oncology, and osteoporosis detection. This article reviews the fundamental principles of radiomic analysis, the current literature relating to the spine, and the limitations of this approach.
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