Predicting cervical cancer biopsy results using demographic and epidemiological parameters: a custom stacked ensemble machine learning approach

Krishnaraj Chadaga, Srikanth Prabhu, Niranjana Sampathila, Rajagopala Chadaga, Swathi K S, Saptarshi Sengupta

Open source

DOI: 10.1080/23311916.2022.2143040
Published: 12
Container: Cogent Engineering
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1080/23311916.2022.2143040,
  title = {Predicting cervical cancer biopsy results using demographic and epidemiological parameters: a custom stacked ensemble machine learning approach},
  author = {Krishnaraj Chadaga and Srikanth Prabhu and Niranjana Sampathila and Rajagopala Chadaga and Swathi K S and Saptarshi Sengupta},
  year = {2022},
  journal = {Cogent Engineering},
  doi = {10.1080/23311916.2022.2143040},
  url = {https://doi.org/10.1080/23311916.2022.2143040}
}

RIS

TY  - JOUR
TI  - Predicting cervical cancer biopsy results using demographic and epidemiological parameters: a custom stacked ensemble machine learning approach
AU  - Krishnaraj Chadaga
AU  - Srikanth Prabhu
AU  - Niranjana Sampathila
AU  - Rajagopala Chadaga
AU  - Swathi K S
AU  - Saptarshi Sengupta
PY  - 2022
JO  - Cogent Engineering
DO  - 10.1080/23311916.2022.2143040
UR  - https://doi.org/10.1080/23311916.2022.2143040
ER  -

APA

Chadaga, K., Prabhu, S., Sampathila, N., Chadaga, R., S, S. K., & Sengupta, S. (2022). Predicting cervical cancer biopsy results using demographic and epidemiological parameters: a custom stacked ensemble machine learning approach. Cogent Engineering. https://doi.org/10.1080/23311916.2022.2143040

Source records

doaj · retrieved 2026-09-26T05:04:54.181Z