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예측모형의 머신러닝 방법론과 통계학적 방법론의 비교: 영상의학 연구에서의 적용
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. I...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748465/ https://www.ncbi.nlm.nih.gov/pubmed/36545410 http://dx.doi.org/10.3348/jksr.2022.0111 |
Sumario: | 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 learning, and statistical learning. Finally, we discussed several considerations for choosing the prediction modeling method. |
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