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Learning Health Systems Seminar is now Informatics in Action!
The Wake Forest Center for Biomedical Informatics will host Arezoo Movaghar, PhD, for her presentation:
Computational Phenotyping and AI-assisted Pre-Screening for Fragile X Associated Disorders
Friday, May 5, 2023
Noon to 1 p.m.
WebEx Details Below
Bio
Arezoo Movaghar, PhD, is a postdoctoral research associate at the University of Wisconsin, Madison. The focus of her translational and interdisciplinary research is on developing innovative and accessible diagnosis and prognosis frameworks for different neurological conditions. She utilizes artificial intelligence (AI) approaches, population-level electronic health records (EHRs) and longitudinal biopsychosocial data to characterize the clinical risk associated with complex neurological conditions. Her research has contributed to understanding the phenotypic manifestation of various alleles of the FMR1 gene. Dr. Movaghar is an advocate for the inclusion of diverse patient populations in medical and clinical research. She is the principal investigator of multiple grants focused on investigating diagnostic odyssey and health disparities in patients with fragile X syndrome. She is specifically interested in identifying factors contributing to health inequalities in patients. Her work has been published in scientific journals such as Science Advances, Genetics in Medicine, Nature Methods, Movement Disorders, and JAMA Network Open. Dr. Movaghar research will significantly advance the knowledge of various neurological conditions, brings advancements of AI in genetic research, and offers a potential pathway to earlier diagnosis and intervention.
Abstract
Neurological disorders (NDs) are the number one cause of disability and the second leading cause of death globally. They are often multi-system conditions with variable prevalence and severity across patients. Due to the complexity of the diseases, many NDs are underdiagnosed, causing delay in access to treatment and services. The availability of big biomedical data in conjunction with advancements in artificial intelligence (AI) offers an unprecedented opportunity to characterize the clinical risk of various NDs leading to development of more effective and patient-centered diagnostic and prognostic practices.
In this presentation, we will investigate the impact of Fragile X associated disorders (FXDs) on health. FXDs are a group of complex inherited genetic conditions caused by full mutation or partial mutation of the Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene. Currently, no approved pharmacological treatment is available for these conditions, and the full extent of their impact on health is unknown. By mining the EHRs from more than 3.8 million patients, we identified new phenotypes associated with FXDs and developed an artificial intelligence (AI)-assisted pre-screening tool capable of identifying potentially undiagnosed cases. Our approach will assist in acceleration of the diagnostic process and will lead to more equitable detection of cases across different patient populations.
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