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王瀚苑, 赵之滢, 宫婷婷, 赵玉虹, 吴琪俊. 机器学习在卵巢癌诊断与预后中应用的研究进展[J]. 肿瘤防治研究, 2021, 48(8): 804-808. DOI: 10.3971/j.issn.1000-8578.2021.20.1396
引用本文: 王瀚苑, 赵之滢, 宫婷婷, 赵玉虹, 吴琪俊. 机器学习在卵巢癌诊断与预后中应用的研究进展[J]. 肿瘤防治研究, 2021, 48(8): 804-808. DOI: 10.3971/j.issn.1000-8578.2021.20.1396
WANG Hanyuan, ZHAO Zhiying, GONG Tingting, ZHAO Yuhong, WU Qijun. Research Progress on Application of Machine Learning in Diagnosis and Prognosis of Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2021, 48(8): 804-808. DOI: 10.3971/j.issn.1000-8578.2021.20.1396
Citation: WANG Hanyuan, ZHAO Zhiying, GONG Tingting, ZHAO Yuhong, WU Qijun. Research Progress on Application of Machine Learning in Diagnosis and Prognosis of Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2021, 48(8): 804-808. DOI: 10.3971/j.issn.1000-8578.2021.20.1396

机器学习在卵巢癌诊断与预后中应用的研究进展

Research Progress on Application of Machine Learning in Diagnosis and Prognosis of Ovarian Cancer

  • 摘要: 妇科恶性肿瘤之一的卵巢癌对女性健康存在严重威胁。机器学习将统计学和计算机学交叉融合,研究人员将机器学习方法应用于卵巢癌诊断及预后研究,旨在提高临床诊断水平和改善患者预后。本文对机器学习在卵巢癌诊断和预后方面的应用进行综述,结果表明,机器学习模型在卵巢癌诊断和预后方面的预测能力均优于传统统计学模型,但未来需要在前瞻性大规模研究中对各类模型进一步测试和验证。

     

    Abstract: Ovarian cancer, one of the gynecological malignancies, poses a serious threat to women's health. The machine learning combines statistics and computer science. Researchers apply the machine learning to the clinical diagnosis and prognosis research of ovarian cancer. This article reviews the applications of machine learning in ovarian cancers. The results show that the predictive ability of machine learning models is better than traditional statistical models, but further test and verification are needed in prospective large-scale studies.

     

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