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Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images.
Front Aging Neurosci. 2017 May 18;9:146. doi: 10.3389/fnagi.2017.00146. eCollection 2017.
Front Aging Neurosci. 2017.
PMID: 28572766
Free PMC article.
A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts.
Gomez-Cabrero D, Walter S, Abugessaisa I, Miñambres-Herraiz R, Palomares LB, Butcher L, Erusalimsky JD, Garcia-Garcia FJ, Carnicero J, Hardman TC, Mischak H, Zürbig P, Hackl M, Grillari J, Fiorillo E, Cucca F, Cesari M, Carrie I, Colpo M, Bandinelli S, Feart C, Peres K, Dartigues JF, Helmer C, Viña J, Olaso G, García-Palmero I, Martínez JG, Jansen-Dürr P, Grune T, Weber D, Lippi G, Bonaguri C, Sinclair AJ, Tegner J, Rodriguez-Mañas L; FRAILOMIC initiative.
Gomez-Cabrero D, et al.
Geroscience. 2021 Jun;43(3):1317-1329. doi: 10.1007/s11357-021-00334-0. Epub 2021 Feb 18.
Geroscience. 2021.
PMID: 33599920
Free PMC article.
This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (identified as robust (R), pre-frail (P), or frail (F)] from the Toledo Study of Healthy Aging (R=178/P=184/F=109), 3 City Bordeaux …
This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (iden …
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