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Example CHIR Common Model Disorder Frame Instantiation

Guy DivitaGuy Divita

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使用情境

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關於

This 509-node CHIR Common Model Disorder Frame Instantiation mind map demonstrates how SHARP snippets are encoded using the CHIR Common Model for clinical NLP. It covers utterance parsing with lexical elements, phrases, and clinical statements, including a concrete example: 'presents for evaluation of a left-sided facial droop'. Key nodes like 'lexicalElements', 'Phrase', and 'Clinical Statement' illustrate the model's structure. The template also notes missing features such as 'A place for a semantic type' and 'ability to include both kind of phrase and cliincail statement'. This CHIR Common Model template serves as a cheat sheet for researchers and developers working on clinical text annotation.

使用條款

何時使用此範本

Clinical NLP researchers and software engineers

Designing a clinical NLP annotation pipeline that requires encoding SHARP snippets into a structured model.

Biomedical informaticians and ontology developers

Reviewing the CHIR Common Model's coverage for disorder frame instantiation before extending it.

Educators and technical writers in health informatics

Teaching or documenting how clinical statements and observations are represented in a standardized framework.

如何使用此範本

步驟 1

Explore the CHIR Common Model Structure

Open the template in Xmind to navigate the 509-node tree and examine how lexical elements, phrases, and clinical statements are structured within the utterance branches.

步驟 2

Identify Model Gaps and Annotate Data

Review the existing model gaps in the 'Things missing' branch and add your own clinical utterances to the map following the established annotation patterns.

步驟 3

Export and Share Your Clinical Findings

Utilize the Xmind export feature to save your customized clinical NLP model as an image or PDF for documentation and research sharing.

常見問題

It provides an example of encoding SHARP clinical snippets using the CHIR Common Model, showing how utterances, lexical elements, phrases, and clinical statements are structured for NLP annotation.

The utterance is broken into lexical elements with POS tags, spans, and tokens. It also includes phrase-level annotations like 'Observation' with coded entries and final mappings.

They highlight limitations such as the absence of a semantic type field, the need to support both phrase types and clinical statements, and questions about code system utility.

Yes, you can edit the .xmind file to add your own clinical utterances, modify lexical element details, or extend the model with new branches for semantic types.

Clinical NLP researchers, biomedical informaticians, and developers working on SHARP or CHIR-based annotation systems will find this template useful for understanding the model's structure.

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