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Regularized Machine Learning Models for Prediction of Metabolic Syndrome Using GCKR, APOA5, and BUD13 Gene Variants: Tehran Cardiometabolic Genetic Study.
Alipour, Nadia; Kazemnejad, Anoshirvan; Akbarzadeh, Mahdi; Eskandari, Farzad; Zahedi, Asiyeh Sadat; Daneshpour, Maryam S.
Affiliation
  • Alipour N; Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
  • Kazemnejad A; Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran. Email: kazem_an@modares.ac.ir.
  • Akbarzadeh M; Cellular and Molecular Endocrine Research Centre, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Eskandari F; Department of Statistics, Faculty of Statistics, Mathematics and Computer, Allameh Tabataba'i University, Tehran, Iran.
  • Zahedi AS; Cellular and Molecular Endocrine Research Centre, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Daneshpour MS; Cellular and Molecular Endocrine Research Centre, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Email: daneshpour@sbmu.ac.ir.
Cell J ; 25(8): 536-545, 2023 Aug 01.
Article in En | MEDLINE | ID: mdl-37641415
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Cell J Year: 2023 Document type: Article Affiliation country: Iran Country of publication: Iran
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Cell J Year: 2023 Document type: Article Affiliation country: Iran Country of publication: Iran