A Journey of Deep Neural Networks for short and long text understanding

October 22, 2019
Free for AMIA members; $50 for non-members
Yuan Luo, PhD

This talk will cover our recent work on developing deep learning algorithms with applications to biomedical narrative text. The common theme of these studies aims at building models that improve prediction accuracy by exploring and combining relational information in text.

The talk will focus on concrete examples including biomedical relation extraction (short text understanding) from clinical notes and document classification (long text understanding). In each example, Dr. Luo will show how to automatically build relational information into a graph representation and how to learn features from graphs. Depending on the nature of the task, heavier machinery of convolutional or recurrent neural networks become necessary to reliably capture important features. Dr. Luo will demonstrate that these methods lead to progressively improved performance by integrating lexical, syntactic and semantic information.

Learning Objectives

After participating in this activity, the learner should be better able to:

  • Understand the use of NLP for clinical work
  • Utilize deep learning in NLP

Speaker Information

Yuan Luo, PhD
Assistant Professor
Northwestern University

Yuan Luo is an Assistant Professor at the Department of Preventive Medicine, Division of Health & Biomedical Informatics at Feinberg School of Medicine in Northwestern University, with courtesy appointments in IEMS and EECS. He earned his PhD degree from MIT EECS with a math minor and a certificate in Graduate Education of Medical Science (GEMS). His research interests include machine learning, natural language processing, time series analysis, computational phenotyping and integrative genomics, with a focus on medical applications. His PhD Thesis was awarded the inaugural Doctoral Dissertation Award Honorable Mention by American Medical Informatics Association (AMIA) in 2017. He won the first prize at the NLP Doctoral Consortium in 2013 during the AMIA Annual Symposium. He is currently an editor with JBI, Plos One and JAMIA Open and was on the Student Editorial Board for JAMIA. He co-chairs eMERGE NLP WG, serves on the AMIA Membership and Outreach Committee, and Bluhm Cardiovascular Institute Research/Innovation and Education Committee. He has served as PC members for top AI and informatics conferences including AAAI, IJCAI, AMIA, AMIA Joint Summits, IEEE ICHI, ACM BCB, CIKM etc. He gave multiple plenary talks including at AMIA Annual Symposium 2017 and at China National Cancer Center in 2018.