예측모형의 머신러닝 방법론과 통계학적 방법론의 비교: 영상의학 연구에... (Korean)

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  • Author(s): 유리하; 한경화
  • Source:
    Journal of the Korean Society of Radiology (2951-0805); Nov2022, Vol. 83 Issue 6, p1219-1228, 10p
  • Additional Information
    • Alternate Title:
      Statistical Model for Prediction Modelling: Application in Medical Imaging Research. (English)
    • Abstract:
      Clinical prediction models has been increasingly published in radiology research. In particular, as a radiomics research is being actively conducted, the prediction model is developed based on the traditional statistical model, as well as machine learning, to account for the high-dimensional data. In this review, we investigated the statistical and machine learning methods used in clinical prediction model research, and briefly summarized each analytical method for statistical model, machine learn)ing, and statistical learning. Finally, we discussed several considerations for choosing the prediction modeling method. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Journal of the Korean Society of Radiology (2951-0805) is the property of Korean Society of Radiology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)