Noémie Elhadad, PhD
Associate Professor of Biomedical Informatics
Dr. Elhadad’s research is in biomedical informatics, natural language processing, and data mining. I develop techniques that aim to support clinicians, patients, and health researchers in their information workflow by automatically extracting and making accessible information from unstructured, large clinical datasets (e.g., the electronic patient record), patient platforms (e.g., online health communities), and quantified self. My research relies on two types of methods: (1) I design novel computational approaches that infer models of health phenomena and account for the specific biases of large health data; (2) I translate the learned models into actionable knowledge and robust systems within the healthcare ecosystem (e.g., a patient record summarization system for clinicians at the point of care). Current projects include patient record summarization and large-scale probabilistic phenotyping based on clinical records, building shared annotated lexical resources (ShARe) for clinical natural language processing, and building tools to facilitate content analysis of online health communities. Dr. Elhadad is part of the OHDSI NLP Working Group.
Rajesh Ranganath, Adler Perotte, Noémie Elhadad, David Blei. The Survival Filter: Joint Survival Analysis with a Latent Time Series. 2015. UAI. Amsterdam, Netherlands.
Adler Perotte, Rajesh Ranganath, Jamie Hirsch, David Blei, Noémie Elhadad.Risk Prediction for Chronic Kidney Disease Progression Using Heterogeneous Electronic Health Record Data and Time Series Analysis. 2015. Journal of the American Medical Informatics Association (JAMIA).
Jamie Hirsch, Jessica Tanenbaum, Sharon Lipsky Gorman, Connie Liu, Eric Schmitz, Dritan Hashorva, Artem Ervits, David Vawdrey, Marc Sturm, Noémie Elhadad. HARVEST, a Longitudinal Patient Record Summarizer. 2015. Journal of the American Medical Informatics Association (JAMIA). 22(2):263-274.
Sameer Pradhan, Noémie Elhadad, Brett South, David Martinez, Lee Christensen, Amy Vogel, Hanna Suominen, Wendy Chapman, Guergana Savova. Evaluating the State of the Art in Disorder Recognition and Normalization of Clinical Narrative. 2015. Journal of the American Medical Informatics Association (JAMIA). 22(1):143-154.
Yolanda Hagar, David Albers, Rimma Pivovarov, Vanja Dukic, and Noémie Elhadad. Survival Analysis Adapted for Electronic Health Record Data: Experiments with Chronic Kidney Disease. 2014. Statistical Analysis and Data Mining. 7(5):385-403.
Rimma Pivovarov, David Albers, Jorge Sepulveda, George Hripcsak, and Noémie Elhadad. Temporal Trends of Hemoglobin A1c Testing. 2014. Journal of the American Medical Informatics Association (JAMIA). 21:1038-1044.
Rimma Pivovarov, David Albers, Jorge Sepulveda, and Noémie Elhadad. Identifying and Mitigating Biases in EHR Laboratory Tests. 2014. Journal of Biomedical Informatics. 51:24-34.