Code-Free AutoML for Binary Classification of Fractured and Non-fractured Bone Radiographs From a Heterogeneous Public Dataset Using Google Cloud Vertex AI: A Proof-of-Concept Study
- DOI
- 10.7759/cureus.115047
- Published
- 2026-08-23
- Container
- Cureus
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.7759/cureus.115047,
title = {Code-Free AutoML for Binary Classification of Fractured and Non-fractured Bone Radiographs From a Heterogeneous Public Dataset Using Google Cloud Vertex AI: A Proof-of-Concept Study},
author = {Mark A Bachir and Neel Nawathey and Alexander Bachir and Akshay J Reddy and Jasmeen K Cheema and Rakesh Patel},
year = {2026},
journal = {Cureus},
doi = {10.7759/cureus.115047},
url = {https://doi.org/10.7759/cureus.115047}
}RIS
TY - JOUR TI - Code-Free AutoML for Binary Classification of Fractured and Non-fractured Bone Radiographs From a Heterogeneous Public Dataset Using Google Cloud Vertex AI: A Proof-of-Concept Study AU - Mark A Bachir AU - Neel Nawathey AU - Alexander Bachir AU - Akshay J Reddy AU - Jasmeen K Cheema AU - Rakesh Patel PY - 2026 JO - Cureus DO - 10.7759/cureus.115047 UR - https://doi.org/10.7759/cureus.115047 ER -
APA
Bachir, M. A., Nawathey, N., Bachir, A., Reddy, A. J., Cheema, J. K., & Patel, R. (2026). Code-Free AutoML for Binary Classification of Fractured and Non-fractured Bone Radiographs From a Heterogeneous Public Dataset Using Google Cloud Vertex AI: A Proof-of-Concept Study. Cureus. https://doi.org/10.7759/cureus.115047
Source records
- crossref · retrieved 2026-09-25T02:36:28.602Z