Integrative and deep learning-based prediction of therapy response in ovarian cancer
- DOI
- 10.1186/s13046-025-03554-w
- Published
- 2025-11-28
- Container
- Journal of Experimental & Clinical Cancer Research
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1186/s13046-025-03554-w,
title = {Integrative and deep learning-based prediction of therapy response in ovarian cancer},
author = {Alicja Rajtak and Ilona Skrabalak and Natalia Ćwilichowska-Puślecka and Agnieszka Kwiatkowska-Makuch and Marcin Poręba and Natalia Skrzypczak and Alicja Krasowska and Michael Pitter and Tomasz Maj and Jan Kotarski and Karolina Okla},
year = {2025},
journal = {Journal of Experimental \& Clinical Cancer Research},
doi = {10.1186/s13046-025-03554-w},
url = {https://doi.org/10.1186/s13046-025-03554-w}
}RIS
TY - JOUR TI - Integrative and deep learning-based prediction of therapy response in ovarian cancer AU - Alicja Rajtak AU - Ilona Skrabalak AU - Natalia Ćwilichowska-Puślecka AU - Agnieszka Kwiatkowska-Makuch AU - Marcin Poręba AU - Natalia Skrzypczak AU - Alicja Krasowska AU - Michael Pitter AU - Tomasz Maj AU - Jan Kotarski AU - Karolina Okla PY - 2025 JO - Journal of Experimental & Clinical Cancer Research DO - 10.1186/s13046-025-03554-w UR - https://doi.org/10.1186/s13046-025-03554-w ER -
APA
Rajtak, A., Skrabalak, I., Ćwilichowska-Puślecka, N., Kwiatkowska-Makuch, A., Poręba, M., Skrzypczak, N., Krasowska, A., Pitter, M., Maj, T., Kotarski, J., & Okla, K. (2025). Integrative and deep learning-based prediction of therapy response in ovarian cancer. Journal of Experimental & Clinical Cancer Research. https://doi.org/10.1186/s13046-025-03554-w
Source records
- crossref · retrieved 2026-09-25T19:41:28.194Z