Measuring the quality of AI-generated clinical notes: A systematic review and experimental benchmark of evaluation methods.
- DOI
- 10.1016/j.artmed.2026.103421
- Published
- 2026-04-07
- Container
- Artif Intell Med
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.artmed.2026.103421,
title = {Measuring the quality of AI-generated clinical notes: A systematic review and experimental benchmark of evaluation methods.},
author = {Dahlberg A and Käenniemi T and Winther-Jensen T and Tapiola O and Luisto R and Puranen T and Gordon M and Sanmark E and Vartiainen V.},
year = {2026},
journal = {Artif Intell Med},
doi = {10.1016/j.artmed.2026.103421},
url = {https://doi.org/10.1016/j.artmed.2026.103421}
}RIS
TY - JOUR TI - Measuring the quality of AI-generated clinical notes: A systematic review and experimental benchmark of evaluation methods. AU - Dahlberg A AU - Käenniemi T AU - Winther-Jensen T AU - Tapiola O AU - Luisto R AU - Puranen T AU - Gordon M AU - Sanmark E AU - Vartiainen V. PY - 2026 JO - Artif Intell Med DO - 10.1016/j.artmed.2026.103421 UR - https://doi.org/10.1016/j.artmed.2026.103421 ER -
APA
A, D., T, K., T, W., O, T., R, L., T, P., M, G., E, S., & V., V. (2026). Measuring the quality of AI-generated clinical notes: A systematic review and experimental benchmark of evaluation methods.. Artif Intell Med. https://doi.org/10.1016/j.artmed.2026.103421
Source records
- europe-pmc · retrieved 2026-09-26T11:25:32.320Z