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Pathology reports are a primary source of information for cancer registries, which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this talk we will present an update on the NCI-DOE pilot for cancer surveillance, discussing deep learning technology developed and highlighting both theoretical and practical perspectives that are relevant to natural language processing of clinical reports. Using different deep learning architectures, we will present benchmark studies for various information extraction tasks and discuss their importance in supporting a comprehensive and scalable national cancer surveillance program. |
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Date: Wednesday, January 17, 2018
Time: 11 AM – 12 PM ET
Room: TE-408/410
WebEx: https://cbiit.webex.com/cbiit/onstage/g.php?MTID=e9389556f3fb2a98e6bdc040843062276
Event Number: 739 172 845
Event Password: $Peakerseries18
You are invited to listen to Drs. Tourassi and Fearn's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Drs. Tourassi and Fearn will give their presentation onsite at Shady Grove.
Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist 
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About the NCI CBIIT Speaker Series:
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