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Monica Agrawal
Software Engineering Intern at Flatiron Health
I am a third year PhD student at MIT CSAIL, advised by David Sontag in
the Clinical Machine Learning group.
the Clinical Machine Learning group.
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If you are Monica Agrawal — please contact us
If you are Monica Agrawal — please contact us
I am a third year PhD student at MIT CSAIL, advised by David Sontag in the Clinical Machine Learning group.
In my research, I tackle various challenges within clinical natural language processing, including:
Clinical entity normalization
Extraction from longitudinal clinical notes
Creation of smarter electronic health records
Previously, I earned a BS and MS in Computer Science at Stanford. While there, I researched in the SNAP Group under Jure Leskovec and Marinka Zitnik, where I used biological networks to predict disease-gene associations and polypharmacy side effects. I've also had internship stints at Google (2015, 2017) and Flatiron Health (2016, 2018).
I am passionate about issues surrounding diversity in computer science. I recently completed my term as an officer for GW6 (Graduate Women in Course 6 at MIT), and I'm on the Dean of Engineering's graduate advisory committee for Diversity, Equity, and Inclusion.
In my research, I tackle various challenges within clinical natural language processing, including:
Clinical entity normalization
Extraction from longitudinal clinical notes
Creation of smarter electronic health records
Previously, I earned a BS and MS in Computer Science at Stanford. While there, I researched in the SNAP Group under Jure Leskovec and Marinka Zitnik, where I used biological networks to predict disease-gene associations and polypharmacy side effects. I've also had internship stints at Google (2015, 2017) and Flatiron Health (2016, 2018).
I am passionate about issues surrounding diversity in computer science. I recently completed my term as an officer for GW6 (Graduate Women in Course 6 at MIT), and I'm on the Dean of Engineering's graduate advisory committee for Diversity, Equity, and Inclusion.
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B18 Robust Benchmarking for Machine Learning of Clinical Entity Extraction
Monica Agrawal
Software Engineering Intern at Flatiron Health
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August 7, 2020, Online, Los Angeles, CA, USA
Machine Learning for Healthcare
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B14 Fast, Structured Clinical Documentation via Contextual Autocomplete
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Steven Horng
Associate Director, Multi-disciplinary Fellowship in Clinical Informatics at Beth Israel Deaconess Medical Center
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David Sontag
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Steven Horng
Associate Director, Multi-disciplinary Fellowship in Clinical Informatics at Beth Israel Deaconess Medical Center
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