Enhancing the positive predictive value of early-stage ovarian cancer detection using a two-step machine learning framework.
- DOI
- 10.1186/s12967-026-08539-7
- Published
- 2026 Jul 1
- Container
- Journal of translational medicine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s12967-026-08539-7,
title = {Enhancing the positive predictive value of early-stage ovarian cancer detection using a two-step machine learning framework.},
author = {Mikami M and Tanabe K and Nagaki S and Nogami Y and Imanishi T and Ikeda M and Yoshida H and Hasegawa M and Shimada M and Shigeta S and Ishikawa M and Kato M and Saji H and Kobayashi Y and Morisada T and Suzuki N and Ohhara T and Tanaka K and Murakami I and Katahira T and Hayashi C and Grubbs BH and Yamagami W and Matsuo K},
year = {2026},
journal = {Journal of translational medicine},
doi = {10.1186/s12967-026-08539-7},
url = {https://doi.org/10.1186/s12967-026-08539-7}
}RIS
TY - JOUR TI - Enhancing the positive predictive value of early-stage ovarian cancer detection using a two-step machine learning framework. AU - Mikami M AU - Tanabe K AU - Nagaki S AU - Nogami Y AU - Imanishi T AU - Ikeda M AU - Yoshida H AU - Hasegawa M AU - Shimada M AU - Shigeta S AU - Ishikawa M AU - Kato M AU - Saji H AU - Kobayashi Y AU - Morisada T AU - Suzuki N AU - Ohhara T AU - Tanaka K AU - Murakami I AU - Katahira T AU - Hayashi C AU - Grubbs BH AU - Yamagami W AU - Matsuo K PY - 2026 JO - Journal of translational medicine DO - 10.1186/s12967-026-08539-7 UR - https://doi.org/10.1186/s12967-026-08539-7 ER -
APA
M, M., K, T., S, N., Y, N., T, I., M, I., H, Y., M, H., M, S., S, S., M, I., M, K., H, S., Y, K., T, M., N, S., T, O., K, T., I, M., T, K., C, H., BH, G., W, Y., & K, M. (2026). Enhancing the positive predictive value of early-stage ovarian cancer detection using a two-step machine learning framework.. Journal of translational medicine. https://doi.org/10.1186/s12967-026-08539-7
Source records
- pubmed · retrieved 2026-09-25T14:20:03.221Z