| Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan R Pomponio, G Erus, M Habes, J Doshi, D Srinivasan, E Mamourian, ... NeuroImage 208, 116450, 2020 | 350 | 2020 |
| MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide VM Bashyam, G Erus, J Doshi, M Habes, IM Nasrallah, M Truelove-Hill, ... Brain 143 (7), 2312-2324, 2020 | 239 | 2020 |
| Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning GB Chand, DB Dwyer, G Erus, A Sotiras, E Varol, D Srinivasan, J Doshi, ... Brain 143 (3), 1027-1038, 2020 | 216 | 2020 |
| The Brain Chart of Aging: machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 … M Habes, R Pomponio, H Shou, J Doshi, E Mamourian, G Erus, ... Alzheimer's & Dementia 17 (1), 89-102, 2021 | 113 | 2021 |
| Association of intensive vs standard blood pressure control with magnetic resonance imaging biomarkers of alzheimer disease: secondary analysis of the SPRINT MIND randomized trial IM Nasrallah, SA Gaussoin, R Pomponio, S Dolui, G Erus, CB Wright, ... JAMA neurology 78 (5), 568-577, 2021 | 52 | 2021 |
| Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage, 208, Article 116450 R Pomponio, G Erus, M Habes, J Doshi, D Srinivasan, E Mamourian, ... | 40 | 2019 |
| Harmonizing functional connectivity reduces scanner effects in community detection AA Chen, D Srinivasan, R Pomponio, Y Fan, IM Nasrallah, SM Resnick, ... NeuroImage 256, 119198, 2022 | 25 | 2022 |
| Mid-life epigenetic age, neuroimaging brain age, and cognitive function: coronary artery risk development in young adults (CARDIA) study Y Zheng, M Habes, M Gonzales, R Pomponio, I Nasrallah, S Khan, ... Aging (Albany NY) 14 (4), 1691, 2022 | 18 | 2022 |
| Brain age and Alzheimer's-like atrophy are domain-specific predictors of cognitive impairment in Parkinson's disease D Charisse, G Erus, R Pomponio, M Gorges, N Schmidt, C Schneider, ... Neurobiology of aging 109, 31-42, 2022 | 17 | 2022 |
| iSTAGING consortium, the Preclinical AD consortium, the ADNI, and the CARDIA studies. The brain chart of aging: machine-learning analytics reveals links between brain aging … M Habes, R Pomponio, H Shou, J Doshi, E Mamourian, G Erus, ... Alzheimers Dement 17 (1), 89-102, 2021 | 17 | 2021 |
| Disentangling Alzheimer’s disease neurodegeneration from typical brain ageing using machine learning G Hwang, A Abdulkadir, G Erus, M Habes, R Pomponio, H Shou, J Doshi, ... Brain Communications 4 (3), fcac117, 2022 | 12 | 2022 |
| Harmonization of large multi-site imaging datasets: Application to 10,232 MRIs for the analysis of imaging patterns of structural brain change throughout the lifespan R Pomponio, G Erus, M Habes, J Doshi, D Srinivasan, E Mamourian, ... bioRxiv, 784363, 2019 | 4 | 2019 |
| Impact of the COVID‐19 pandemic on chronic disease management and patient reported outcomes in patients with pulmonary hypertension: The Pulmonary Hypertension Association Registry M Mayer, DB Badesch, KH Nielsen, S Kawut, T Bull, JJ Ryan, J Sager, ... Pulmonary Circulation 13 (2), e12233, 2023 | 1 | 2023 |
| Machine‐learning based MRI neuro‐anatomical signatures associated with cardiovascular and metabolic risk factors ST Govindarajan, E Mamourian, G Erus, A Abdulkadir, R Melhem, J Doshi, ... Alzheimer's & Dementia 18, e067709, 2022 | 1 | 2022 |
| Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals I Skampardoni, IM Nasrallah, A Abdulkadir, J Wen, R Melhem, ... JAMA psychiatry 81 (5), 456-467, 2024 | | 2024 |
| Mid‐life epigenetic age, neuroimaging brain age, and cognitive decline: Coronary Artery Risk Development in Young Adults (CARDIA) Study Y Zheng, M Habes, MM Gonzales, R Pomponio, IM Nasrallah, ... Alzheimer's & Dementia 17, e050078, 2021 | | 2021 |
| MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14468 individuals worldwide (vol 143, pg 2312, 2020) VM Bashyam, G Erus, J Doshi, M Habes, IM Nasrallah, M Truelove-Hill, ... BRAIN 144, 2021 | | 2021 |
| Erratum: MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide (Brain (2020) 143 (2312-2324 VM Bashyam, G Erus, J Doshi, M Habes, I Nasralah, M Truelove-Hill, ... Brain 144 (1), e12, 2021 | | 2021 |
| A predictive, modeling‐based screening tool to enrich amyloid beta positivity in a cognitively normal sample: Biomarkers (non‐neuroimaging)/Use in clinical trial design and … M Truelove‐Hill, G Erus, R Pomponio, V Bashyam, J Doshi, M Habes, ... Alzheimer's & Dementia 16, e045242, 2020 | | 2020 |
| Prediction of longitudinal clinical outcomes of MCI population using Alzheimer’s AT [N] biomarker profiling: Can machine learning methods improve our predictions? Biomarkers … A Ezzati, DJ Harvey, C Davatzikos, M Truelove‐Hill, LP Sreepada, ... Alzheimer's & Dementia 16, e041125, 2020 | | 2020 |
