- STAGES - Machine Translation (MT):
Funded by the NSF.
STAGES is a joint machine translation project that involving Brandeis University, Columbia University,
Information Science Institute at the University of Southern California, The University of Colorado at
Boulder, and The University of Rochester.
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- CLAMR - Cross-Linguistic AMR's
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MiPACQ:
Funded by the NIH.
- Multi-source Integrated Platform for Answering Clinical Questions
MiPACQ is a question answering project. It is a project designed to build a system through which doctors
can ask a computer questions about existing medical records and information sources to get answers
quickly and efficiently. This project is a joint effort of the University of Colorado at Boulder, the
Mayo Clinic, and the Harvard School.
- EPIC:
Funded by the NSF.
Project EPIC applies natural language processing techniques in order to facilitate computer mediated
communication during times of crisis.
- SHARP:
Funded by HHS
The SHARP project at Colorado aims to merge and standardize patient data from non-electronic forms, such as the free
text of radiology and pathology notes, into an electronic health record (EHR). The project applies natural
language processing techniques to extract structured information from clinical notes that allows the
information contained there to be searched, e.g. for a diagnosis, compared, e.g. to find common co-morbidities
with a certain diagnosis, and summarized. The project will help improve patient care by reducing
inconsistencies in patient data, providing physicians with more accurate and uniform information in a
centralized location.
- THYME:
Funded by NIH
The THYME project aims to identify clinical events like diseases, symptoms
and treatments and recognize their ordering along a timeline. Specifically, it aims to develop an annotation
schema for temporal relations in clinical free text, create an annotated corpus of clinical text following
the schema, develop new algorithms for training temporal relation discovery systems on this corpus and
evaluate these systems on various use cases, including clinical notes on colon cancer and radiology reports
on brain tumors.
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