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Arezoo Movaghar

TitleAssistant Professor
InstitutionWake Forest School of Medicine
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    Arezoo Movaghar, PhD, is an Assistant Professor in the Department of Pediatrics and Center for Artificial Intelligence Research at Wake Forest University, School of Medicine. She obtained her PhD in Biomedical Informatics from the University of Wisconsin-Madison.

    The focus of her research is on developing innovative and accessible diagnosis and prognosis frameworks for complex disorders. She employs artificial intelligence (AI) techniques, electronic health records, and biopsychosocial data in her research. She has a special interest in identifying factors contributing to diagnostic disparities and health inequalities in patients. Her work contributes to the development of AI-assisted pre-screening approaches for complex disorders that can lead to more equitable detection of cases across various patient populations.

    Overall, her research offers insights into clinical risks associated with various conditions, brings advancements of AI in genetic research, and provides a potential pathway to early diagnosis and intervention.

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    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Movaghar A, Page D, Brilliant M, Mailick M. Advancing artificial intelligence-assisted pre-screening for fragile X syndrome. BMC Med Inform Decis Mak. 2022 Jun 10; 22(1):152. PMID: 35689224.
    2. Movaghar A, Page D, Brilliant M, Mailick M. Prevalence of Underdiagnosed Fragile X Syndrome in 2 Health Systems. JAMA Netw Open. 2021 Dec 01; 4(12):e2141516. PMID: 34967885.
    3. Movaghar A, Page D, Saha K, Rynn M, Greenberg J. Machine learning approach to measurement of criticism: The core dimension of expressed emotion. J Fam Psychol. 2021 Oct; 35(7):1007-1015. PMID: 34410788.
    4. Movaghar A, Page D, Scholze D, Hong J, DaWalt LS, Kuusisto F, Stewart R, Brilliant M, Mailick M. Artificial intelligence-assisted phenotype discovery of fragile X syndrome in a population-based sample. Genet Med. 2021 Jul; 23(7):1273-1280. PMID: 33772223.
    5. Movaghar A, Page D, Brilliant M, Baker MW, Greenberg J, Hong J, DaWalt LS, Saha K, Kuusisto F, Stewart R, Berry-Kravis E, Mailick MR. Data-driven phenotype discovery of FMR1 premutation carriers in a population-based sample. Sci Adv. 2019 Aug; 5(8):eaaw7195. PMID: 31457090.
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