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Get Free AccessTT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.
Nada Assi, Aurélie Moskal, Nadia Slimani, Vivian Viallon, Véronique Chajès, Heinz Freisling, Stefano Monni, Sven Knueppel, Jana Förster, Elisabete Weiderpass, Leila Luján‐Barroso, Pilar Amiano, Eva Ardanáz, Esther Molina‐Montes, Diego Salmerón, J. Ramón Quirós, Anja Olsen, Anne Tjønneland, Christina C. Dahm, Kim Overvad, Laure Dossus, A. Fournier, Laura Baglietto, Renée T. Fortner, Rudolf Kaaks, Antonia Trichopoulou, Christina Bamia, Philippos Orfanos, Maria Santucci de Magistris, Giovanna Masala, Claudia Agnoli, Fulvio Ricceri, Rosario Tumino, H. Bas Bueno de Mesquita, Marije F. Bakker, Petra H. Peeters, Guri Skeie, Tonje Braaten, Anna Winkvist, Ingegerd Johansson, Kay‐Tee Khaw, Nicholas J. Wareham, Tim Key, Ruth C. Travis, Julie A. Schmidt, Melissa A. Merritt, Elio Riboli, Isabelle Romieu, Pietro Ferrari (2015). A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). , 19(2), DOI: https://doi.org/10.1017/s1368980015000294.
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Type
Article
Year
2015
Authors
49
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1017/s1368980015000294
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