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예측모형의 머신러닝 방법론과 통계학적 방법론의 비교: 영상의학 연구에서의 적용
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ryu, Leeha | - |
| dc.contributor.author | Han, Kyunghwa | - |
| dc.date.accessioned | 2026-01-20T02:39:45Z | - |
| dc.date.available | 2026-01-20T02:39:45Z | - |
| dc.date.created | 2026-01-14 | - |
| dc.date.issued | 2022-11 | - |
| dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/210015 | - |
| dc.description.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 learning, and statistical learning. Finally, we discussed several considerations for choosing the prediction modeling method. | - |
| dc.language | 한국어 | - |
| dc.publisher | KOREAN SOCIETY OF RADIOLOGY | - |
| dc.relation.isPartOf | JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY | - |
| dc.title | 예측모형의 머신러닝 방법론과 통계학적 방법론의 비교: 영상의학 연구에서의 적용 | - |
| dc.title.alternative | [Machine Learning vs. Statistical Model for Prediction Modelling: Application in Medical Imaging Research] | - |
| dc.type | Article | - |
| dc.contributor.googleauthor | Ryu, Leeha | - |
| dc.contributor.googleauthor | Han, Kyunghwa | - |
| dc.identifier.doi | 10.3348/jksr.2022.0111 | - |
| dc.identifier.pmid | 36545410 | - |
| dc.subject.keyword | Precision Medicine | - |
| dc.subject.keyword | Medical Imaging | - |
| dc.subject.keyword | Clinical Decision Rules | - |
| dc.subject.keyword | Machine Learning | - |
| dc.contributor.affiliatedAuthor | Han, Kyunghwa | - |
| dc.identifier.scopusid | 2-s2.0-85188527793 | - |
| dc.identifier.wosid | 001222938600008 | - |
| dc.citation.volume | 83 | - |
| dc.citation.number | 6 | - |
| dc.citation.startPage | 1219 | - |
| dc.citation.endPage | 1228 | - |
| dc.identifier.bibliographicCitation | JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY, Vol.83(6) : 1219-1228, 2022-11 | - |
| dc.identifier.rimsid | 90985 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 1 | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordAuthor | Precision Medicine | - |
| dc.subject.keywordAuthor | Medical Imaging | - |
| dc.subject.keywordAuthor | Clinical Decision Rules | - |
| dc.subject.keywordAuthor | Machine Learning | - |
| dc.subject.keywordPlus | INDIVIDUAL PROGNOSIS | - |
| dc.subject.keywordPlus | DIAGNOSIS TRIPOD | - |
| dc.subject.keywordPlus | EVENTS | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.relation.journalWebOfScienceCategory | Radiology, Nuclear Medicine & Medical Imaging | - |
| dc.relation.journalResearchArea | Radiology, Nuclear Medicine & Medical Imaging | - |
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