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Volumn 14, Issue 1, 2013, Pages

Using a multi-staged strategy based on machine learning and mathematical modeling to predict genotype-phenotype risk patterns in diabetic kidney disease: A prospective case-control cohort analysis

Author keywords

Diabetic kidney disease; Genotypes; Machine learning; Phenotypes; Prediction; Random forest; Support vector machine

Indexed keywords

ANGIOTENSIN RECEPTOR ANTAGONIST; ANTILIPEMIC AGENT; CHOLESTEROL; DIPEPTIDYL CARBOXYPEPTIDASE INHIBITOR; INSULIN; LIPID; LOW DENSITY LIPOPROTEIN CHOLESTEROL; TRIACYLGLYCEROL; UTEROGLOBIN;

EID: 84880335873     PISSN: None     EISSN: 14712369     Source Type: Journal    
DOI: 10.1186/1471-2369-14-162     Document Type: Article
Times cited : (54)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.