Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.

Doshi A, Marche C, Chernyavskiy P, Glass G, Hartka T

DOI: 10.1080/15389588.2024.2356663
Published: 2024
Container: Traffic injury prevention
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1080/15389588.2024.2356663,
  title = {Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.},
  author = {Doshi A and Marche C and Chernyavskiy P and Glass G and Hartka T},
  year = {2024},
  journal = {Traffic injury prevention},
  doi = {10.1080/15389588.2024.2356663},
  url = {https://doi.org/10.1080/15389588.2024.2356663}
}

RIS

TY  - JOUR
TI  - Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.
AU  - Doshi A
AU  - Marche C
AU  - Chernyavskiy P
AU  - Glass G
AU  - Hartka T
PY  - 2024
JO  - Traffic injury prevention
DO  - 10.1080/15389588.2024.2356663
UR  - https://doi.org/10.1080/15389588.2024.2356663
ER  -

APA

A, D., C, M., P, C., G, G., & T, H. (2024). Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.. Traffic injury prevention. https://doi.org/10.1080/15389588.2024.2356663

Source records

pubmed · retrieved 2026-09-26T15:44:09.253Z