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Machine learning-based diagnosis of uterine myomas and sarcomas using tumor-educated platelet transcriptomics:a retrospective multicenter study
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作者 Xudong Liu Roujie Huang +27 位作者 Hua Yang Yu Dong Lei Li Zhe Li Jia Zeng Qingxia Zhang Yun Liu Lei Zhang Yidi Ma Lin Zhang Weijie Tian Yan You Yaqian Li Tianshu Sun Xiaoyue Zhao Wei Liu Le Dang Zhibo Zhang Lei Li Ran Chen Yining Zhao Yiming Liang Baochen Du Qijun Xu Xuwo Ji Yuxing Dai Han Liang Lan Zhu 《Science Bulletin》 2026年第1期60-63,共4页
Uterine myomas are the most prevalent benign gynecological tumors,affecting over 70%of women[1].They are often associated with significant morbidity,including anemia and infertility.In contrast,uterine sarcomas,althou... Uterine myomas are the most prevalent benign gynecological tumors,affecting over 70%of women[1].They are often associated with significant morbidity,including anemia and infertility.In contrast,uterine sarcomas,although rare,are highly malignant,with a five-year survival rate of 50%-55%in early stages and a stark decline to 8%-12%in advanced stages[2],[3]. 展开更多
关键词 uterine sarcomas uterine myomas benign gynecological tumorsaffecting diagnosis retrospective multicenter study tumor educated platelets machine learning transcriptomics
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