Artificial intelligence for automated ICD-10 coding: a systematic review of multi-label text classification in clinical narratives

Kamonrat Tangudomkit, Sawrawit Chairat, Sitthichok Chaichulee

Open source

DOI: 10.3389/fdgth.2026.1905379
Published: 2026-08-13
Container: Frontiers in Digital Health
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/fdgth.2026.1905379,
  title = {Artificial intelligence for automated ICD-10 coding: a systematic review of multi-label text classification in clinical narratives},
  author = {Kamonrat Tangudomkit and Sawrawit Chairat and Sitthichok Chaichulee},
  year = {2026},
  journal = {Frontiers in Digital Health},
  doi = {10.3389/fdgth.2026.1905379},
  url = {https://doi.org/10.3389/fdgth.2026.1905379}
}

RIS

TY  - JOUR
TI  - Artificial intelligence for automated ICD-10 coding: a systematic review of multi-label text classification in clinical narratives
AU  - Kamonrat Tangudomkit
AU  - Sawrawit Chairat
AU  - Sitthichok Chaichulee
PY  - 2026
JO  - Frontiers in Digital Health
DO  - 10.3389/fdgth.2026.1905379
UR  - https://doi.org/10.3389/fdgth.2026.1905379
ER  -

APA

Tangudomkit, K., Chairat, S., & Chaichulee, S. (2026). Artificial intelligence for automated ICD-10 coding: a systematic review of multi-label text classification in clinical narratives. Frontiers in Digital Health. https://doi.org/10.3389/fdgth.2026.1905379

Source records

crossref · retrieved 2026-09-25T16:44:22.791Z