PRODUCTS
PRODUCTS
For NLP Development and Deployment:
For NLP Development and Deployment:

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The CLAMP GUI(Graphical User Interface) system provides not only high-performance NLP modules and pipelines customized for clinical text, but also user-friendly interfaces for quickly building customized NLP pipelines. It provides multiple useful features for NLP professionals.
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Annotate local data and re-train machine learning models with a few clicks
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Specify rules on the top of ML models to improve performance
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Export NLP pipelines as web services for easy integration
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Provide Java APIs for individual components for system integration
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CLAMP components are built on proven methods in many clinical NLP challenges
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Identify context of entities such as negation, certainty, and values
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Support Multi-threads/Multi-processes/Docker/Distributed systems
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Process local files/Database tables/HDFS files

Designed for efficient text annotation with high-quality, to support information extraction tasks, including named entity recognition, relation extraction and concept normalization.
- Time saving
- Automatically annotate text based on user uploaded dictionaries and deep learning models
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Automatically define annotation schema based on existing annotations
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Automatically structure and index annotation guidelines
- Multiple format support
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Accommodate annotation formats of multiple existing annotation tools, such as prodigy, MAE, brat, etc.
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Both text and pdf files can be annotated
- Multiple data sources: Files, Databases
- Quality insurance
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Interface for progress management, inter-annotator agreement check and discrepancy resolving
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Automatically detect ambiguous, missing and conflicting annotations

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DeepMed Docker
- DeepMed for SaaS
For NLP Applications:

By leveraging state-of-the-art information retrieval and information extraction technologies, Vital provides a powerful yet user-friendly platform for quickly searching millions of clinical documents in EHRs, thus to efficiently identify cohorts of patients of interest, as well as specific phenotypes for each patient in a cohort.
Use cases of Vital include healthcare quality reporting, disease registry curation, and clinical and translational research. Our studies have shown that Vital dramatically improves efficiency of manual chart review in both operational and research tasks.
- Schedule processing tasks
- Allocate computational resources for each task
- Search and visualize outputs of NLP outputs
- Support Common Data Models (CDM) such as OMOP CDM

These pipelines include Cancer pipeline, Substance Overdose pipeline, Social Determinants pipeline, and many more...