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ICD-10-PCS Clinical Terminology Mapper

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Databricks2025-12-05 收录
下载链接:
https://marketplace.databricks.com/details/8d791844-f1df-4ed9-82b4-555f858a2944/John-Snow-Labs_ICD-10-PCS-Clinical-Terminology-Mapper
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资源简介:
**ICD-10-PCS Clinical Terminology Mapper** The ICD-10-PCS Resolver Pipeline is designed to extract Procedure entities from clinical texts and map them to their corresponding ICD-10-PCS codes. This pipeline ensures accurate identification and coding of medical procedures, facilitating efficient clinical documentation and analysis. Procedure Extraction: Identifies Procedure entities within unstructured clinical narratives. **Key Features** - Automated Procedure Coding: Automatically extracts and maps procedures mentioned in clinical narratives to standardized ICD-10-PCS codes, supporting accurate and complete clinical documentation. - Enhanced Billing Accuracy: Helps ensure correct ICD-10-PCS coding for procedures, reducing claim denials and improving revenue cycle performance. - Structured Data Generation: Converts unstructured clinical text into structured ICD-10-PCS codes, enabling more reliable analysis and reporting on procedural trends and outcomes. - Standardized Procedure Representation: Facilitates decision-making by mapping free-text procedures to a standardized format that can be integrated into CDS systems. **Additional Model Information** - [Full model info on John Snow Labs Models Hub](https://nlp.johnsnowlabs.com/2024/02/02/icd10pcs_resolver_pipeline_en.html) - **Domain:** Clinical Text Analysis - **Subdomain:** Terminology Codes - **Predictable entities:** ICD-10-PCS **How to run this model:** 1. Acquire a John Snow Labs license from [Sales](mailto:sales@johnsnowlabs.com) 2. Import this listing. 3. See the attached notebook to deploy and use the model. This model comes with optimized CPU and GPU builds. You can select which one to deploy via the notebook.
提供机构:
John Snow Labs
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集是一个ICD-10-PCS临床术语映射器,能够从临床文本中自动提取医疗程序实体并映射到标准化的ICD-10-PCS代码。它旨在提高临床文档的准确性和计费效率,同时将非结构化文本转换为结构化代码,以支持更可靠的分析和报告。
以上内容由遇见数据集搜集并总结生成
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