Deep Learning for Clinical Natural Language Processing
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  Sadid Hasan   Sadid Hasan
Senior Scientist, Artificial Intelligence Laboratory
Philips Research North America


Tuesday, January 31, 2017
01:30 PM - 02:15 PM

Level:  Technical - Intermediate

Humans use language as a way to express their feelings and communicate with each other. Due to the rapid growth of unstructured electronic data over the last decade, Natural Language Processing (NLP) has become one of the most important technologies of this information age. Similarly, the ever-increasing amount of Electronic Health Record (EHR) clinical free text documents has urged the need to build novel clinical NLP solutions towards optimizing the patient outcomes across the care continuum. Recently, Deep Learning (DL) techniques have demonstrated superior performance over the traditional Machine Learning (ML) techniques for many different NLP tasks. DL models are able to automatically learn representations of data and thus, do not require any traditional domain-specific feature engineering. This talk will present a brief intuitive overview of how DL algorithms can be applied to solve NLP problems, followed by a discussion on various DL-driven clinical NLP applications developed in the Artificial Intelligence lab at Philips Research - such as diagnostic inferencing from unstructured clinical narratives, and clinical paraphrase generation.

Dr. Sadid Hasan is a Senior Scientist in the Artificial Intelligence Laboratory at Philips Research North America (Cambridge, Massachusetts). His research interests span a wide range of topics in the areas of Computational Linguistics, Natural Language Processing (NLP), Artificial Intelligence, and Machine Learning. His recent work includes solving problems related to clinical question answering and paraphrase generation using Deep Learning algorithms. Before joining Philips, he was a Post-Doctoral Fellow at the Department of Mathematics and Computer Science, University of Lethbridge, Canada, from where he also obtained his PhD. in Computer Science in 2013 (with a focus in Computational Linguistics, Natural Language Processing, and Machine Learning). Dr. Hasan has around 40 publications in the top NLP/Machine Learning conferences, workshops, and journals, where he also regularly serves as a reviewer/program committee member including NIPS, ClinicalNLP, AISTATS, NAACL, AMIA, TKDE and JAIR.

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