Artificial intelligence effectivity in fracture detection

V. Boginskis, S. Zadoroznijs, I. Cernavska, D. Beikmane, J. Sauka

Open source

DOI: 10.26641/2307-0404.2023.3.288965
Published: 2023-09-29
Container: Medicni perspektivi
Publisher: Dnipro State Medical University
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.26641/2307-0404.2023.3.288965,
  title = {Artificial intelligence effectivity in fracture detection},
  author = {V. Boginskis and S. Zadoroznijs and I. Cernavska and D. Beikmane and J. Sauka},
  year = {2023},
  journal = {Medicni perspektivi},
  doi = {10.26641/2307-0404.2023.3.288965},
  url = {https://doi.org/10.26641/2307-0404.2023.3.288965}
}

RIS

TY  - JOUR
TI  - Artificial intelligence effectivity in fracture detection
AU  - V. Boginskis
AU  - S. Zadoroznijs
AU  - I. Cernavska
AU  - D. Beikmane
AU  - J. Sauka
PY  - 2023
JO  - Medicni perspektivi
DO  - 10.26641/2307-0404.2023.3.288965
UR  - https://doi.org/10.26641/2307-0404.2023.3.288965
ER  -

APA

Boginskis, V., Zadoroznijs, S., Cernavska, I., Beikmane, D., & Sauka, J. (2023). Artificial intelligence effectivity in fracture detection. Medicni perspektivi. https://doi.org/10.26641/2307-0404.2023.3.288965

Source records

crossref · retrieved 2026-09-26T22:09:26.320Z