Towards robust medical machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles

Adan Rotteveel, Wen-Yee Lee, Zoi Kountouri, Nikolas Stefanou, Howard Kivell, Clifford Gluck, Shuguang Zhang, Andreas Mershin

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DOI: 10.1101/2024.11.19.624273
Published: 2024-11-21
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Publisher: openRxiv
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Cite this work

BibTeX

@article{allodium:10.1101/2024.11.19.624273,
  title = {Towards robust medical machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles},
  author = {Adan Rotteveel and Wen-Yee Lee and Zoi Kountouri and Nikolas Stefanou and Howard Kivell and Clifford Gluck and Shuguang Zhang and Andreas Mershin},
  year = {2024},
  doi = {10.1101/2024.11.19.624273},
  url = {https://doi.org/10.1101/2024.11.19.624273}
}

RIS

TY  - JOUR
TI  - Towards robust medical machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles
AU  - Adan Rotteveel
AU  - Wen-Yee Lee
AU  - Zoi Kountouri
AU  - Nikolas Stefanou
AU  - Howard Kivell
AU  - Clifford Gluck
AU  - Shuguang Zhang
AU  - Andreas Mershin
PY  - 2024
DO  - 10.1101/2024.11.19.624273
UR  - https://doi.org/10.1101/2024.11.19.624273
ER  -

APA

Rotteveel, A., Lee, W., Kountouri, Z., Stefanou, N., Kivell, H., Gluck, C., Zhang, S., & Mershin, A. (2024). Towards robust medical machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles. https://doi.org/10.1101/2024.11.19.624273

Source records

crossref · retrieved 2026-09-26T09:51:27.871Z