Comparison of machine-learning algorithms for the prediction of Current Procedural Terminology (CPT) codes from pathology reports-Reference-Cited by-同舟云学术

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Comparison of machine-learning algorithms for the prediction of Current Procedural Terminology (CPT) codes from pathology reports

Published:2022 Issue: Volume:13 Page:100165
ISSN:2153-3539
Container-title:Journal of Pathology Informatics
language:en
Short-container-title:Journal of Pathology Informatics

Author:

Levy Joshua,Vattikonda Nishitha,Haudenschild Christian,Christensen Brock,Vaickus Louis

Publisher

Elsevier BV

Subject

Computer Science Applications,Health Informatics,Pathology and Forensic Medicine

Reference63 articles.

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2. Automated ancillary cancer history classification for mesothelioma patients from free-text clinical reports;Wilson;J Pathol Inform,2010

3. Natural language processing of clinical notes on chronic diseases: Systematic review;Sheikhalishahi;JMIR Med Inform,2019

4. The revival of the notes field: Leveraging the unstructured content in electronic health records;Assale;Front Med (Lausanne),2019

5. Clinical text data in machine learning: systematic review;Spasic;JMIR Med Inform,2020

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1. Evaluating the Efficacy of Large Language Models in CPT Coding for Craniofacial Surgery: A Comparative Analysis;Journal of Craniofacial Surgery;2024-09-02

2. Replicating Current Procedural Terminology code assignment of rhinology operative notes using machine learning;World Journal of Otorhinolaryngology - Head and Neck Surgery;2024-05-28

3. Applications of Large Language Models in Pathology;Bioengineering;2024-03-31

4. Systematic evaluation of common natural language processing techniques to codify clinical notes;PLOS ONE;2024-03-07

5. TCGA-Reports: A machine-readable pathology report resource for benchmarking text-based AI models;Patterns;2024-03

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