Correction: Development and Assessment of a Custom Multilabel Classifier for ICD-10–Based Classification of Primary Care Text Data

Overview

This report addresses a correction regarding the authorship attribution in a previously published study on a multilabel classifier for ICD-10 classification. The correction clarifies the joint contribution of senior authors OS and VvW.

Background

Accurate billing methodologies are crucial in healthcare for financial viability and proper compensation for services rendered. The classification of clinical documentation, particularly in primary care, is essential for effective billing and coding, which is governed by standards such as ICD-10.

Data Highlights

No numerical or trial data is presented in this correction notice.

Key Findings

• The correction adds an asterisk to the names of senior authors OS and VvW.
• A footnote clarifying their joint contribution has been included in the metadata.
• The Acknowledgments section has been updated to reflect the senior authorship.
• The corrected article has been resubmitted to PubMed and other repositories.

Clinical Implications

This correction ensures proper attribution of contributions in research, which is important for academic integrity and recognition in the field. Accurate authorship is essential for the credibility of published studies.

Conclusion

The correction enhances the clarity of authorship in the study on ICD-10 classification, reinforcing the importance of accurate representation in academic publications.

Related Resources & Content

1. JMIR Medical Informatics, 2026 -- Automated ICD-10–Anchored Classification of Primary Care Text Data: Development and Evaluation of a Custom Multilabel Classifier
2. European Radiology (Springer) — Comparison of proprietary and fine-tuned large language models for multi-label classification of billing codes from radiology reports
3. European Radiology — Utilizing Transformer Models for Organizing Unstructured Radiology Report Databases
4. npj Digital Medicine — Assessment of a Commercial Deep Learning System's Effectiveness in Detecting Intracranial Hemorrhage in Clinical Practice
5. European Radiology — Creation of Image-Centric Decision Support Systems Leveraging Data from Radiological Free-Text Report Databases Using Text-Based Transformers
6. ICD-10-CM Official Guidelines for Coding and Reporting
7. JMIR Medical Informatics - Automated ICD-10–Anchored Classification of Primary Care Text Data: Development and Evaluation of a Custom Multilabel Classifier
8. HTI-1 Final Rule - ONC - Office of the National Coordinator for Health Information Technology