Monitoring and early warning of ovarian cancer using high-dimensional non-parametric EWMA control chart based on sliding window

Monitoring and early warning of ovarian cancer using high-dimensional non-parametric EWMA control chart based on sliding window

Abstract Ovarian tumors are a common ovarian dysfunction that affects women’s daily lives. Although ovarian tumors are generally sensitive to chemotherapy and initially respond well to platinum/taxane-based treatments, the postoperative recurrence rate remains high in advanced cases. Many researcher...

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Bibliographic Details
Main Authors: Bin Wu, Wen Zhong, Yixing Ren, Zhongli Zhou, Liu Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Statistical process control
Benign ovarian tumors
Ovarian cancer
Empirical likelihood ratio test
EWMA
Online Access:https://doi.org/10.1038/s41598-025-86576-w
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https://doi.org/10.1038/s41598-025-86576-w

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