Identifying ovarian cancer with machine learning DNA methylation pattern analysis
Abstract The majority of patients with epithelial ovarian cancer (EOC) continue to be diagnosed at an advanced stage despite great advances in this disease treatment. To impact overall survival, we need better methods of EOC early diagnosis. We performed a case control study to predict high-grade se...
Saved in:
| Main Authors: | Jesus Gonzalez Bosquet, Vincent M. Wagner, Douglas Russo, Henry D. Reyes, Andreea M. Newtson, David P. Bender, Michael J. Goodheart |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-05460-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Investigating the effect of optimal cytoreduction in the context of platinum sensitivity in high‐grade serous ovarian cancer
by: Nicholas Cardillo, et al.
Published: (2022-10-01) -
Profiling of Circulating Cell-free DNA Methylation Patterns Identifies Aberrant Methylated CTBP1 Promotor Sites for Prediction of Alzheimer’s Disease
by: Zhiwu Dong, et al.
Published: (2025-04-01) -
DNA methylation patterns in cord blood DNA and body size in childhood.
by: Caroline L Relton, et al.
Published: (2012-01-01) -
Heterogeneous DNA methylation status in same-cell subpopulations of ovarian cancer tissues
by: Qiling Li, et al.
Published: (2017-05-01) -
Potential use of DNA methylation in cervical swabs for early ovarian cancer diagnosis
by: Edyta Biskup, et al.
Published: (2025-02-01)