Causal inference and NLP applied to healthcare data
Join us on the 26 of April for an online meetup featuring Aaron Kaufman, an Assistant Professor of Computational Social Science at New York University Abu Dhabi. As an expert in the field, Kaufman will share his research on the applications of ML and NLP in social, behavioral, and medical sciences. He will delve into the intersection of these tools with causal inference statistics and provide insights into using low-tech NLP methods to improve data quality and program evaluation.
During the talk, Kaufman will discuss three specific uses of NLP in the same workflow: missing data imputation, causal matching, and heterogeneous effect estimation. He will show how simple NLP tools can improve all three aspects, without requiring extensive mathematical knowledge.
The talk will be valuable for anyone involved in applied NLP, A/B testing, ML, Data Science or health data.
Don’t miss this opportunity to learn from Kaufman’s extensive experience in the field. This event promises to be informative and engaging, and attendees will leave with a deeper understanding of how to use NLP to improve data quality and program evaluation. Join us on the 26 of April to participate in this exciting online meetup!
When? 26 of April 19:00
Language: English
100% of the funds from ticket sales will be transferred to the charity fund Children of Heroes for warm needs of children who lost their parents because of russian aggression on the territory of Ukraine.