Name: Deep Learning for Clinical Natural Language Processing
Start: 2019-09-11T18:00:00-04:00
End: 2019-09-11T20:00:00-04:00
Location: CIC Cambridge @ 245 Main

Speaker: Dr. Sadid Hasan, Senior Scientist and Technical Lead of the AI Group at Philips Research
https://www.linkedin.com/in/sadidhasan/

Topic:
Deep Learning for Clinical Natural Language Processing

Schedule:
6:00pm - 6:30pm - ODSC Intro, Pizza & Refreshments
6:30pm - 7:20pm - Talk
7:20pm - 7:30pm - Q&A
7:30pm - 8:00pm - Networking

Bio:
Dr. Sadid Hasan is a Senior Scientist and Technical Lead of the Artificial Intelligence Group at Philips Research, Cambridge, MA. His recent research focuses on various Natural Language Processing (NLP) problems related to Clinical Information Extraction, Text Classification, Natural Language Inference, Clinical Text Summarization, and Paraphrase Generation using Deep Learning. Prior to joining Philips, Sadid was a Post Doctoral Fellow at the Department of Mathematics and Computer Science, University of Lethbridge, Canada, from where he obtained his PhD. in Computer Science with a focus in NLP and Machine Learning. Sadid has over 60 peer-reviewed publications in the top NLP/Machine Learning venues, where he also regularly serves as a program committee member/area chair including ACL, IJCAI, EMNLP, NeurIPS, ICML, etc.

Abstract:
The ever-increasing amount of Electronic Health Record (EHR) clinical free text documents has urged the need to build novel clinical natural language processing (NLP) solutions towards optimizing the patient outcomes across the care continuum. In this talk, I will discuss some of the recent deep learning-based clinical NLP algorithms developed in the Artificial Intelligence Lab at Philips Research such as radiology report classification, clinical paraphrase generation and text simplification, and disease named entity recognition, etc.

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Deep Learning for Clinical Natural Language Processing

CIC Cambridge @ 245 Main

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ODSC Data Science Boston

Deep Learning for Clinical Natural Language Processing

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