Supervised machine learning tools: a tutorial for clinicians LL Vercio, K Amador, JJ Bannister, S Crites, A Gutierrez, ME MacDonald, ... Journal of Neural Engineering 17 (6), 062001, 2020 | 116 | 2020 |
Using machine learning to predict dementia from neuropsychiatric symptom and neuroimaging data S Gill, P Mouches, S Hu, D Rajashekar, FP MacMaster, EE Smith, ... Journal of Alzheimer's Disease 75 (1), 277-288, 2020 | 96 | 2020 |
A statistical atlas of cerebral arteries generated using multi-center MRA datasets from healthy subjects P Mouches, ND Forkert Scientific data 6 (1), 29, 2019 | 61 | 2019 |
Neural correlates of the impulse dyscontrol domain of mild behavioral impairment S Gill, M Wang, P Mouches, D Rajashekar, T Sajobi, FP MacMaster, ... International Journal of Geriatric Psychiatry 36 (9), 1398-1406, 2021 | 60 | 2021 |
Multimodal biological brain age prediction using magnetic resonance imaging and angiography with the identification of predictive regions P Mouches, M Wilms, D Rajashekar, S Langner, ND Forkert Human brain mapping 43 (8), 2554-2566, 2022 | 36 | 2022 |
High-resolution T2-FLAIR and non-contrast CT brain atlas of the elderly D Rajashekar, M Wilms, ME MacDonald, J Ehrhardt, P Mouches, ... Scientific Data 7 (1), 56, 2020 | 26 | 2020 |
Detecting brain network communities: Considering the role of information flow and its different temporal scales LM Sanchez-Rodriguez, Y Iturria-Medina, P Mouches, RC Sotero NeuroImage 225, 117431, 2021 | 25 | 2021 |
Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study HL Carlson, BT Craig, AJ Hilderley, J Hodge, D Rajashekar, P Mouches, ... NeuroImage: Clinical 28, 102508, 2020 | 23 | 2020 |
Investigating the relationship between the SNCA gene and cognitive abilities in idiopathic Parkinson’s disease using machine learning M Ramezani, P Mouches, E Yoon, D Rajashekar, JA Ruskey, E Leveille, ... Scientific Reports 11 (1), 4917, 2021 | 19 | 2021 |
Fairness-related performance and explainability effects in deep learning models for brain image analysis EAM Stanley, M Wilms, P Mouches, ND Forkert Journal of Medical Imaging 9 (6), 061102-061102, 2022 | 18 | 2022 |
Explainable classification of Parkinson’s disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets M Camacho, M Wilms, P Mouches, H Almgren, R Souza, R Camicioli, ... NeuroImage: Clinical 38, 103405, 2023 | 17 | 2023 |
Invertible modeling of bidirectional relationships in neuroimaging with normalizing flows: application to brain aging M Wilms, JJ Bannister, P Mouches, ME MacDonald, D Rajashekar, ... IEEE Transactions on Medical Imaging 41 (9), 2331-2347, 2022 | 16 | 2022 |
Unifying brain age prediction and age-conditioned template generation with a deterministic autoencoder P Mouches, M Wilms, D Rajashekar, S Langner, N Forkert Medical Imaging with Deep Learning, 497-506, 2021 | 13 | 2021 |
Influence of cardiovascular risk-factors on morphological changes of cerebral arteries in healthy adults across the life span P Mouches, S Langner, M Domin, MD Hill, ND Forkert Scientific reports 11 (1), 12236, 2021 | 13 | 2021 |
The association of saliva cytokines and pediatric sports-related concussion outcomes TA Seeger, J Tabor, S Sick, KJ Schneider, C Jenne, P La, AS Talai, ... The Journal of head trauma rehabilitation 35 (5), 354-362, 2020 | 12 | 2020 |
Structural integrity of white matter tracts as a predictor of acute ischemic stroke outcome D Rajashekar, P Mouchès, J Fiehler, BK Menon, M Goyal, AM Demchuk, ... International Journal of Stroke 15 (9), 965-972, 2020 | 11 | 2020 |
Towards self-explainable classifiers and regressors in neuroimaging with normalizing flows M Wilms, P Mouches, JJ Bannister, D Rajashekar, S Langner, ND Forkert Machine Learning in Clinical Neuroimaging: 4th International Workshop, MLCN …, 2021 | 10 | 2021 |
Bidirectional modeling and analysis of brain aging with normalizing flows M Wilms, JJ Bannister, P Mouches, ME MacDonald, D Rajashekar, ... Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro …, 2020 | 10 | 2020 |
Multimodal brain age prediction fusing morphometric and imaging data and association with cardiovascular risk factors P Mouches, M Wilms, A Aulakh, S Langner, ND Forkert Frontiers in Neurology 13, 979774, 2022 | 8 | 2022 |
A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder EAM Stanley, D Rajashekar, P Mouches, M Wilms, K Plettl, ND Forkert Medical Imaging 2022: Computer-Aided Diagnosis 12033, 310-315, 2022 | 7 | 2022 |