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Endometriosis is a chronic, inflammatory, estrogen-dependent disease that has a significant impact on quality of life and is estimated to affect 6-10% of women of reproductive age worldwide. Despite its high prevalence, it is an enigmatic disease: there is currently no cure, no known biomarker or non-invasive diagnostic test for this multifactorial disease. In this talk, Dr. Elhadad will report on ongoing research into two interrelated questions: how to characterize and uncover the different ways endometriosis presents in individuals, primarily by phenotyping the disease, and how to support individuals in discovering self and management. on the disease given its heterogeneous presentations. It will show the current characterization of endometriosis from clinical data sources and discuss its current limitations, in particular the discrepancy with the patient's daily experience of endometriosis. She will present the design and development of a personal health IT solution (a research application called Phendo) and the analysis of data contributed by Phendo participants for endometriosis phenotyping. Finally, she will explain how this data can be further leveraged to help individuals learn about and self-manage their illness, as well as facilitate shared decision-making with their providers.
Noémie Elhadad is an Associate Professor and Interim Co-Director of the Department of Biomedical Informatics at Columbia University, affiliated with the Columbia Department of Computer Science and the Data Science Institute. She received her doctorate in computer science from Columbia University. His research lies at the intersection of machine learning, technology, and medicine. She studies ways in which observational clinical data (e.g., electronic health records) and patient-generated data (e.g., online community health discussions, mobile health data) can improve access to information relevant to patients, clinicians and health researchers and can have an impact on patient care and health. Dr. Elhadad is currently a member of the NLM Biomedical Informatics, Library and Data Sciences Review Committee.
Title NLM: Advancing women's health through data science and personal health informatics / Noémie Elhadad.
Author: Elhadad, Noémie.
National Library of Medicine (United States)
Broadcast date: Wednesday June 12, 2019, 2:00:00 p.m.
The time displayed is Eastern Time, local time in Washington DC.
https://videocast.nih.gov/summary.asp?Live33148&bhcp1
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