Skip to main content
Top
Published in: Journal of Clinical Monitoring and Computing 2/2024

Open Access 04-02-2024 | Editorial

Natural language processing for electronic health records in anaesthesiology: an introduction to clinicians with recommendations and pitfalls

Authors: Martin Bernstorff, Simon Tilma Vistisen, Kenneth C. Enevoldsen

Published in: Journal of Clinical Monitoring and Computing | Issue 2/2024

Login to get access

Excerpt

The application of advanced statistical models has become omnipresent in submissions to medical journals. Great results have been achieved within e.g. imaging segmentation and diagnostics [1], whereas other areas such as prediction models based on Electronic Health Records (EHRs) are still in their infancy when it comes to demonstrating added value [2]. …
Literature
1.
go back to reference Isensee F, Jaeger PF, Kohl SA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18(2):203–11.CrossRefPubMed Isensee F, Jaeger PF, Kohl SA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18(2):203–11.CrossRefPubMed
2.
go back to reference Vistisen ST, Pollard TJ, Harris S, Lauritsen SM. Artificial intelligence in the clinical setting: towards actual implementation of reliable outcome predictions. Eur J Anaesthesiol EJA. 2022;39(9):729–32.CrossRef Vistisen ST, Pollard TJ, Harris S, Lauritsen SM. Artificial intelligence in the clinical setting: towards actual implementation of reliable outcome predictions. Eur J Anaesthesiol EJA. 2022;39(9):729–32.CrossRef
4.
go back to reference Zhong W et al. Improving Case Duration Accuracy of Orthopedic Surgery Using Bidirectional Encoder Representations from Transformers (BERT) on Radiology Reports,., 2023. Zhong W et al. Improving Case Duration Accuracy of Orthopedic Surgery Using Bidirectional Encoder Representations from Transformers (BERT) on Radiology Reports,., 2023.
5.
go back to reference Devlin J, Chang M-W, Lee K, Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota: Association for Computational Linguistics, Jun. 2019, pp. 4171–4186. https://doi.org/10.18653/v1/N19-1423. Devlin J, Chang M-W, Lee K, Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota: Association for Computational Linguistics, Jun. 2019, pp. 4171–4186. https://​doi.​org/​10.​18653/​v1/​N19-1423.
6.
go back to reference Pennington J, Socher R, Manning CD. Glove: Global vectors for word representation, in Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), 2014, pp. 1532–1543. Pennington J, Socher R, Manning CD. Glove: Global vectors for word representation, in Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), 2014, pp. 1532–1543.
8.
go back to reference Vaswani A et al. Attention is all you need. Adv Neural Inf Process Syst, vol. 30, 2017. Vaswani A et al. Attention is all you need. Adv Neural Inf Process Syst, vol. 30, 2017.
Metadata
Title
Natural language processing for electronic health records in anaesthesiology: an introduction to clinicians with recommendations and pitfalls
Authors
Martin Bernstorff
Simon Tilma Vistisen
Kenneth C. Enevoldsen
Publication date
04-02-2024
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 2/2024
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-024-01128-3

Other articles of this Issue 2/2024

Journal of Clinical Monitoring and Computing 2/2024 Go to the issue

Letter to the editor

Letter to the editor