Scalable cloud–AI architecture for synthetic healthcare data generation and anomaly modeling: a simulation-based study

Keshav Kaushik

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DOI: 10.1186/s12982-026-01464-6
Published: 2026-02-02
Container: Discover Public Health
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1186/s12982-026-01464-6,
  title = {Scalable cloud–AI architecture for synthetic healthcare data generation and anomaly modeling: a simulation-based study},
  author = {Keshav Kaushik},
  year = {2026},
  journal = {Discover Public Health},
  doi = {10.1186/s12982-026-01464-6},
  url = {https://doi.org/10.1186/s12982-026-01464-6}
}

RIS

TY  - JOUR
TI  - Scalable cloud–AI architecture for synthetic healthcare data generation and anomaly modeling: a simulation-based study
AU  - Keshav Kaushik
PY  - 2026
JO  - Discover Public Health
DO  - 10.1186/s12982-026-01464-6
UR  - https://doi.org/10.1186/s12982-026-01464-6
ER  -

APA

Kaushik, K. (2026). Scalable cloud–AI architecture for synthetic healthcare data generation and anomaly modeling: a simulation-based study. Discover Public Health. https://doi.org/10.1186/s12982-026-01464-6

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crossref · retrieved 2026-09-25T11:57:40.646Z