Comparative Experimentation of Accuracy Metrics in Automated Medical Reporting: The Case of Otitis Consultations

Wouter Faber, Renske Bootsma, Tom Huibers, Sandra van Dulmen, Sjaak Brinkkemper

2024

Abstract

Generative Artificial Intelligence (AI) can be used to automatically generate medical reports based on transcripts of medical consultations. The aim is to reduce the administrative burden that healthcare professionals face. The accuracy of the generated reports needs to be established to ensure their correctness and usefulness. There are several metrics for measuring the accuracy of AI generated reports, but little work has been done towards the application of these metrics in medical reporting. A comparative experimentation of 10 accuracy metrics has been performed on AI generated medical reports against their corresponding General Practitioner’s (GP) medical reports concerning Otitis consultations. The number of missing, incorrect, and additional statements of the generated reports have been correlated with the metric scores. In addition, we introduce and define a Composite Accuracy Score which produces a single score for comparing the metrics within the field of automated medical reporting. Findings show that based on the correlation study and the Composite Accuracy Score, the ROUGE-L and Word Mover’s Distance metrics are the preferred metrics, which is not in line with previous work. These findings help determine the accuracy of an AI generated medical report, which aids the development of systems that generate medical reports for GPs to reduce the administrative burden.

Paper Citation

in Harvard Style

Faber W., Bootsma R., Huibers T., van Dulmen S. and Brinkkemper S. (2024). Comparative Experimentation of Accuracy Metrics in Automated Medical Reporting: The Case of Otitis Consultations. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 585-594. DOI: 10.5220/0012422300003657

in Bibtex Style

@conference{healthinf24,
author={Wouter Faber and Renske Bootsma and Tom Huibers and Sandra van Dulmen and Sjaak Brinkkemper},
title={Comparative Experimentation of Accuracy Metrics in Automated Medical Reporting: The Case of Otitis Consultations},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={585-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012422300003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Comparative Experimentation of Accuracy Metrics in Automated Medical Reporting: The Case of Otitis Consultations
SN - 978-989-758-688-0
AU - Faber W.
AU - Bootsma R.
AU - Huibers T.
AU - van Dulmen S.
AU - Brinkkemper S.
PY - 2024
SP - 585
EP - 594
DO - 10.5220/0012422300003657
PB - SciTePress