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Thursday, August 23 • 3:00pm - 3:30pm
Using AI on Messy Text Data with Examples from the Medical Domain

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While the medical domain has a wealth of data, much of it is unstructured and poorly formatted. Doctors’ and nurses’ notes are notoriously noisy and often contain incomplete sentences, run-ons, and invented acronyms. This lack of structure in medical text confounds traditional NLP methods that rely on sentence structure to infer entities and relationships. However, this problem is not unique to the medical domain.  Anyone trying to analyze web searches, social media posts, or any poorly formatted text face similar challenges. The core issue is that many NLP methods depend on well formatted text for analysis and break down when dealing with poorly formatted text. In this talk, John and Krishna will present a number of methods that can be used to wrangle messy text for various machine learning and NLP use cases, within and outside of the medical domain.

Speakers
avatar for Krishna Srihasam, PhD

Krishna Srihasam, PhD

Senior Data Scientist, Wolters Kluwer Health
Krishna Srihasam is a senior data scientist at Wolters Kluwer Health. He has been applying ML and AI techniques to Health and Patient data for more than 3 years. He holds a Ph.D in Computational Neuroscience and has published several articles on applying ML techniques to neuroscience... Read More →


Thursday August 23, 2018 3:00pm - 3:30pm
Exec Ed: 426, 428, 430 Boston University Questrom School of Business, 595 Commonwealth Avenue Boston

Attendees (79)