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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.
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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.
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B18 Robust Benchmarking for Machine Learning of Clinical Entity Extraction

Monica Agrawal
Software Engineering Intern at Flatiron Health
+ 4 speakers
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Machine Learning for Healthcare
August 7, 2020, Online, Los Angeles, CA, USA
Machine Learning for Healthcare
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Machine Learning for Healthcare
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B18 Robust Benchmarking for Machine Learning of Clinical Entity Extraction

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Software Engineering Intern at Flatiron Health
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B14 Fast, Structured Clinical Documentation via Contextual Autocomplete

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Divya Gopinath

Research Engineer at TruEra
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Luke Murray

Research Intern at Microsoft
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Steven Horng

Associate Director, Multi-disciplinary Fellowship in Clinical Informatics at Beth Israel Deaconess Medical Center
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