| Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder L Bishop‐Fitzpatrick, A Movaghar, JS Greenberg, D Page, LS DaWalt, ... Autism Research 11 (8), 1120-1128, 2018 | 64 | 2018 |
| Data-driven phenotype discovery of FMR1 premutation carriers in a population-based sample A Movaghar, D Page, M Brilliant, MW Baker, J Greenberg, J Hong, ... Science Advances 5 (8), eaaw7195, 2019 | 37 | 2019 |
| High-content analysis of CRISPR-Cas9 gene-edited human embryonic stem cells J Carlson-Stevermer, M Goedland, B Steyer, A Movaghar, M Lou, ... Stem cell reports 6 (1), 109-120, 2016 | 30 | 2016 |
| Health Profiles of Mosaic Versus Non-mosaic FMR1 Premutation Carrier Mothers of Children With Fragile X Syndrome MR Mailick, A Movaghar, J Hong, JS Greenberg, LS DaWalt, L Zhou, ... Frontiers in genetics 9, 173, 2018 | 22 | 2018 |
| Health profiles of adults with autism spectrum disorder: Differences between women and men LS DaWalt, JL Taylor, A Movaghar, J Hong, B Kim, M Brilliant, MR Mailick Autism Research 14 (9), 1896-1904, 2021 | 20 | 2021 |
| Artificial intelligence–assisted phenotype discovery of fragile X syndrome in a population-based sample A Movaghar, D Page, D Scholze, J Hong, LS DaWalt, F Kuusisto, ... Genetics in Medicine 23 (7), 1273-1280, 2021 | 18 | 2021 |
| Automated screening for Fragile X premutation carriers based on linguistic and cognitive computational phenotypes A Movaghar, M Mailick, A Sterling, J Greenberg, K Saha Scientific reports 7 (1), 2674, 2017 | 16 | 2017 |
| The inconvenience of data of convenience: computational research beyond post-mortem analyses CA Azencott, T Aittokallio, S Roy, T Norman, S Friend, G Stolovitzky, ... Nature methods 14 (10), 937-938, 2017 | 13 | 2017 |
| Advancing artificial intelligence-assisted pre-screening for fragile X syndrome A Movaghar, D Page, M Brilliant, M Mailick BMC Medical Informatics and Decision Making 22 (1), 152, 2022 | 8 | 2022 |
| Prevalence of underdiagnosed fragile X syndrome in 2 health systems A Movaghar, D Page, M Brilliant, M Mailick JAMA Network Open 4 (12), e2141516-e2141516, 2021 | 5 | 2021 |
| FMR1 Low Zone CGG Repeats: Phenotypic Associations in the Context of Parenting Stress MR Mailick, J Hong, LS DaWalt, JS Greenberg, A Movaghar, MW Baker, ... Frontiers in pediatrics 8, 223, 2020 | 4 | 2020 |
| Mild Neurological Signs in FMR1 Premutation Women in an Unselected Community‐Based Cohort MR Mailick, J Hong, A Movaghar, L DaWalt, EM Berry‐Kravis, MH Brilliant, ... Movement Disorders 36 (10), 2378-2386, 2021 | 3 | 2021 |
| Machine learning approach to measurement of criticism: The core dimension of expressed emotion. A Movaghar, D Page, K Saha, M Rynn, J Greenberg Journal of Family Psychology 35 (7), 1007, 2021 | 2 | 2021 |
| Response to Timothé Ménard A Movaghar, D Page, M Brilliant, M Mailick Genetics in Medicine 24 (3), 752-753, 2022 | 1 | 2022 |
| Evolvix BEST Names for semantic reproducibility across code2brain interfaces L Loewe, KS Scheuer, SA Keel, V Vyas, B Liblit, B Hanlon, MC Ferris, ... Annals of the New York Academy of Sciences 1387 (1), 124-144, 2017 | 1 | 2017 |
| Computational Phenotyping Based on Clinical Data and Electronic Health Records for Neurodevelopmental Disorders A Movaghar The University of Wisconsin-Madison, 2019 | | 2019 |
| Symposium Title: Using Electronic Health Records in Research on Neurodevelopmental Disorders: Phenotypic Discovery and Implications for Privacy LS DaWalt, JL Taylor, A Movaghar, J Hong, B Kim, M Brilliant, M Mailick | | |
| 2018 Gatlinburg Conference Poster Submission PS-54 L Bishop-Fitzpatrick, A Movaghar, JS Greenberg, D Page, LS DaWalt, ... | | |
