Exploring acetylation-related gene markers in polycystic ovary syndrome: insights into pathogenesis and diagnostic potential using machine learning

• Главные авторы: Jiqing Wang (Автор), Yuqing Wang (Автор), Shanshan Li (Автор), Xiaoqin Fang (Автор), Chaoyue Zhang (Автор), Zuqing Wang (Автор), Yi Zheng (Автор), Hanzhi Deng (Автор), Shifen Xu (Автор), Yiqun Mi (Автор)
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• Опубликовано: Taylor & Francis Group, 2024-12-01T00:00:00Z.
• Предметы: article
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Objective Polycystic ovary syndrome (PCOS) is a prevalent cause of menstrual irregularities and infertility in women, impacting quality of life. Despite advancements, current understanding of PCOS pathogenesis and treatment remains limited. This study uses machine learning-based data mining to ident...