Supporting Healthcare Professionals With NLP & Accelerating LM Inference by 100%

On March 24th at 7pm, we will have our next virtual meetup with two talks! 🎉 Talk titles: "Supporting decision-making of healthcare professionals with Clinical NLP" by Betty van Aken and "Accelerating Language Model Inference by 100%" by Michel Bartels. As always, we will have smaller breakout room sessions after the talks to connect and discuss. Save the date! Looking forward to meeting you!

"Supporting decision-making of healthcare professionals with Clinical NLP"
by Betty van Aken, PhD Student at Berlin University of Applied Sciences and Technology
Betty's current research focuses on NLP for the medical domain. Specifically she wants to find out how to use patient information in clinical notes to improve decision support systems for medical professionals. In this regard, she wants to build explainable systems that leverage publicly available medical data. Her talk will cover parts of her paper "Outcome Prediction from Clinical Notes at Admission Time" and her recent research on explainability in NLP.

"Accelerating Language Model Inference by 100%"
by Michel Bartels, NLP Engineering Intern at deepset
Michel joined deepset as an intern before going to university and became the team's expert in model compression techniques, in particular model distillation. In this talk, he will explain how every NLP application can benefit from distilled models and give an overview of different available techniques. You will learn how to easily distill a model yourself with just a few lines of code in order to reduce the size of the model without sacrificing prediction quality.