Results 101 to 110 of about 2,991,648 (129)

Food consumption by degree of food processing and risk of type 2 diabetes mellitus: a prospective cohort analysis of the European Prospective Investigation into Cancer and Nutrition (EPIC). [PDF]

Lancet Reg Health Eur
Dicken SJ, Dahm CC, Ibsen DB, Olsen A, Tjønneland A, Louati-Hajji M, Cadeau C, Marques C, Schulze MB, Jannasch F, Baldassari I, Manfredi L, Santucci de Magistris M, Sánchez MJ, Castro-Espin C, Palacios DR, Amiano P, Guevara M, van der Schouw YT, Boer JMA, Verschuren WMM, Sharp SJ, Forouhi NG, Wareham NJ, Vamos EP, Chang K, Vineis P, Heath AK, Gunter MJ, Nicolas G, Weiderpass E, Huybrechts I, Batterham RL.   +32 more
europepmc   +1 more source

Membrane mechanics dictate axonal pearls-on-a-string morphology and function. [PDF]

Nat Neurosci
Griswold JM, Bonilla-Quintana M, Pepper R, Lee CT, Raychaudhuri S, Ma S, Gan Q, Syed S, Zhu C, Bell M, Suga M, Yamaguchi Y, Chéreau R, Nägerl UV, Knott G, Rangamani P, Watanabe S.   +16 more
europepmc   +1 more source

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Casamitjana A, Mancini M, Robinson E, Peter L, Annunziata R, Althonayan J, Crampsie S, Blackburn E, Billot B, Atzeni A, Puonti O, Balbastre Y, Schmidt P, Hughes J, Augustinack JC, Edlow BL, Zöllei L, Thomas DL, Kliemann D, Bocchetta M, Strand C, Holton JL, Jaunmuktane Z, Iglesias JE.   +23 more
europepmc   +1 more source

Sliced Inverse Regression (SIR) via group lasso

Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), 2021
In this paper the authors propose a group-lasso for sliced inverse regression (group lasso-SIR). This proposed method can deal with the problem of correlation existence between predictor variables. Simulation is used to investigate the performance of proposed method comparing with ridge and lasso in sliced inverse regression (lasso-SIR).
Bahr Mohammed, Saif Raheem, Tahir Dikheel   +2 more
openaire   +1 more source

A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction

Neurocomputing, 2018
Dimension reduction is essential in fMRI decoding, but the complex relationship between fMRI data and class labels is often unknown or not well modeled so that the most effective dimension reduction (e.d.r.) directions can hardly be identified.
Li Hu, Z G Zhang
exaly   +2 more sources

Optimal quantization applied to sliced inverse regression

Journal of Statistical Planning and Inference, 2012
Article dans revue internationale à comité de lectureInternational audienceAbstract: In this paper we consider a semiparametric regression model involving a $d$-dimensional quantitative explanatory variable $X$ and including a dimension reduction of $X ...
Romain Azaïs, Jérôme Saracco
exaly   +2 more sources

Sliced inverse regression (SIR): An appraisal of small sample alternatives to slicing

1997
The authors consider the semiparametric regression model \(y=g(x'\beta_1,\dots, x'\beta_k,\epsilon)\), where the dependent variable \(y\) depends on the explanatory variables through so-called indexes, i.e. linear combinations \(x'\beta_i\), \(i=1,\dots,k\).
Aragon, Yves, Saracco, Jérôme
openaire   +2 more sources

BIG-SIR: a Sliced Inverse Regression approach for massive data

Statistics and Its Interface, 2016
Liquet, Benoit, Saracco, Jerome
openaire   +5 more sources

Détection d’individus atypiques en régression SIR (sliced inverse regression)

2021
Saracco, Jérôme, Lorenzo, Hadrien
openaire   +1 more source