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Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Choi, H | - |
| dc.contributor.author | Choi, B | - |
| dc.contributor.author | Park, I | - |
| dc.date.accessioned | 2024-11-19T04:31:34Z | - |
| dc.date.available | 2024-11-19T04:31:34Z | - |
| dc.date.issued | 2024 | - |
| dc.identifier.issn | 0918-2918 | - |
| dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/33476 | - |
| dc.language.iso | en | - |
| dc.subject.MESH | Acute Kidney Injury | - |
| dc.subject.MESH | Aged | - |
| dc.subject.MESH | Contrast Media | - |
| dc.subject.MESH | Female | - |
| dc.subject.MESH | Humans | - |
| dc.subject.MESH | Kidney Diseases | - |
| dc.subject.MESH | Machine Learning | - |
| dc.subject.MESH | Male | - |
| dc.subject.MESH | Middle Aged | - |
| dc.title | Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables | - |
| dc.type | Article | - |
| dc.identifier.pmid | 38296469 | - |
| dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11518587 | - |
| dc.subject.keyword | acute kidney injury | - |
| dc.subject.keyword | contrast-induced nephropathy | - |
| dc.subject.keyword | machine learning | - |
| dc.subject.keyword | percutaneous coronary intervention | - |
| dc.contributor.affiliatedAuthor | Choi, H | - |
| dc.contributor.affiliatedAuthor | Park, I | - |
| dc.type.local | Journal Papers | - |
| dc.identifier.doi | 10.2169/internalmedicine.3308-23 | - |
| dc.citation.title | Internal medicine (Tokyo, Japan) | - |
| dc.citation.volume | 63 | - |
| dc.citation.number | 19 | - |
| dc.citation.date | 2024 | - |
| dc.citation.startPage | 2719 | - |
| dc.citation.endPage | 2719 | - |
| dc.identifier.bibliographicCitation | Internal medicine (Tokyo, Japan), 63(19). : 2719-2719, 2024 | - |
| dc.identifier.eissn | 1349-7235 | - |
| dc.relation.journalid | J009182918 | - |
- Appears in Collections:
- Journal Papers > School of Medicine / Graduate School of Medicine > Nephrology
- Files in This Item:
- 38296469.pdfDownload
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