Statistical models for neuroimaging meta-analytic inference by Salimi-Khorshidi, G

Adjusting the effect of nonstationarity in cluster-based and TFCE inference. by Salimi-Khorshidi, G, Smith, S, Nichols, T

Adjusting the neuroimaging statistical inferences for nonstationarity. by Salimi-Khorshidi, G, Smith, S, Nichols, T

Adjusting the neuroimaging statistical inferences for nonstationarity. by Salimi-Khorshidi, G, Smith, S, Nichols, T

Adjusting the neuroimaging statistical inferences for nonstationarity. by Salimi-Khorshidi, G, Smith, S, Nichols, T

Using Gaussian-process regression for meta-analytic neuroimaging inference based on sparse observations. by Salimi-Khorshidi, G, Nichols, T, Smith, S, Woolrich, M

Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. by Salimi-Khorshidi, G, Smith, S, Keltner, JR, Wager, T, Nichols, T

Investigating the stratified efficacy and safety of pharmacological blood pressure-lowering: an overall protocol for individual patient-level data meta-analyses of over 300 000 ran... by Rahimi, K, Canoy, D, Nazarzadeh, M, Salimi-Khorshidi, G

Untangling the complexity of multimorbidity with machine learning by Hassaine, A, Salimi-Khorshidi, G, Canoy, D, Rahimi, K

A comparative study of model-centric and data-centric approaches in the development of cardiovascular disease risk prediction models in the UK Biobank by Mamouei, M, Fisher, T, Rao, S, Li, Y, Salimi-Khorshidi, G, Rahimi, K

Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. by Salimi-Khorshidi, G, Douaud, G, Beckmann, C, Glasser, M, Griffanti, L, Smith, S

Systolic blood pressure, chronic obstructive pulmonary disease and cardiovascular risk by Rao, S, Nazarzadeh, M, Li, Y, Canoy, D, Mamouei, M, Salimi-Khorshidi, G, Rahimi, K

Network modelling methods for FMRI. by Smith, S, Miller, K, Salimi-Khorshidi, G, Webster, M, Beckmann, C, Nichols, T, Ramsey, J, Woolrich, M

Hi-BEHRT: Hierarchical transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records by Li, Y, Mamouei, M, Salimi-Khorshidi, G, Rao, S, Hassaine, A, Canoy, D, Lukasiewicz, T, Rahimi, K

Meta-analytic evidence for neuroimaging models of depression: State or trait? by Graham, J, Salimi-Khorshidi, G, Hagan, C, Walsh, N, Goodyer, I, Lennox, B, Suckling, J

Meta-analytic evidence for neuroimaging models of depression: state or trait? by Graham, J, Salimi-Khorshidi, G, Hagan, C, Walsh, N, Goodyer, I, Lennox, B, Suckling, J

Investigating the association of environmental exposures and all-cause mortality in the UK Biobank using sparse principal component analysis by Mamouei, M, Zhu, Y, Nazarzadeh, M, Rahimi, K, Hassaine, A, Salimi-Khorshidi, G, Cai, Y

Validation of risk prediction models applied to longitudinal electronic health record data for the prediction of major cardiovascular events in the presence of data shifts by Li, Y, Salimi-Khorshidi, G, Rao, S, Canoy, D, Hassaine, A, Lukasiewicz, T, Rahimi, K, Mamouei, M

Systolic blood pressure and cardiovascular risk in patients with diabetes: a prospective cohort study by Rao, S, Li, Y, Nazarzadeh, M, Canoy, D, Mamouei, M, Hassaine, A, Salimi-Khorshidi, G, Rahimi, K

Targeted-BEHRT: deep learning for observational causal inference on longitudinal electronic health records by Rao, S, Mamouei, M, Salimi-Khorshidi, G, Li, Y, Ramakrishnan, R, Canoy, D, Hassaine, A, Rahimi, K