ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Auto-mapping Clinical Documents to ICD-10 using SNOMED-CT.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Development and Evaluation of SNOMED CT Automated Mapping Tool: Advancing Terminology Standardization and Semantic Interoperability.JMIR medical informatics · 2026Article
- Developing a Thai User Interface Terminology for Systematized Nomenclature of Medicine Clinical Terms Implementation in Primary Care: Cross-Sectional Content Coverage Analysis.JMIR medical informatics · 2026Article
- Experiences With Integrating Medical Terminologies Into User Interfaces for a Decision Support System for Primary Care: Conceptual and Development Study.JMIR medical informatics · 2026Article
- Annotating and indexing scientific articles with rare diseases.Journal of biomedical semantics · 2026Article
- Secondary Use of Clinical Problem List Descriptions for Bi-Encoder Based ICD-10 Classification.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Effectiveness of vitamin D2 compared with vitamin D3 replacement therapy in a primary healthcare setting: a retrospective cohort study.Qatar medical journal · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
Excessive paperwork is a considerable issue that leads to additional burdens for health-care professionals. In Thai health-care systems, physicians manually review medical records to select an appropriate principle diagnosis and other co-morbidities and convert them into ICD-10s to claim financial support from the government. Accordingly, 160,000 ICD-10 codes and 46,000 in-patient discharge summaries are documented by physicians at Maharaj Nakorn Chiang Mai hospital each year. As a result, to decrease physicians' burden of manual paper-work, we created a new approach to automatically analyse discharge summary notes and map the diagnoses to ICD-10s. We combined SNOMED-CT and natural language processing techniques within the approach through 3 steps: cleaning data; extracting keywords from discharge summary notes; and matching keywords to ICD-10. In this paper, we present that mapping clinical documents by using approximate matching and SNOMED-CT shows potential to be used for automating the ICD-10 mapping process.
Indexed as
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34457144PMC8378640What OpenQuestion holds
Registered trials
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