skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Multi-Task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports

Conference ·

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC); Work for Others (WFO)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1329745
Resource Relation:
Journal Volume: 529; Conference: INNS Conference on Big Data, Thessaloniki, Greece, 20161023, 20161025
Country of Publication:
United States
Language:
English

References (8)

Narrative based medicine: Why study narrative? journal January 1999
Information extraction from pathology reports in a hospital setting conference January 2011
Automated Classification of Free-text Pathology Reports for Registration of Incident Cases of Cancer journal January 2012
A unified architecture for natural language processing: deep neural networks with multitask learning conference January 2008
Deep Learning to Predict Patient Future Diseases from the Electronic Health Records
  • Miotto, Riccardo; Li, Li; Dudley, Joel T.
  • Advances in Information Retrieval: 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings https://doi.org/10.1007/978-3-319-30671-1_66
book January 2016
An information-theoretic perspective of tf–idf measures journal January 2003
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups journal November 2012
The WEKA data mining software: an update journal November 2009