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目前临床使用的检验项目多达1000余项，采用逻辑回归二分类和支持向量机分别构建卵巢恶性肿瘤预测模型，探讨检验项目与诊断结果的相关性。实验结果表明，2种机器学习算法构建的卵巢恶性肿瘤预测模型具有较高的预测水平，红细胞体积分布宽度和平均血小板体积等非特异性检验项目与卵巢恶性肿瘤诊断结果具有较强的相关性。
Abstract：There are more than 1000 inspection items currently used in clinical practice. The real laboratory medicine data are used to construct the malignant ovarian tumor prediction model through logistic regression and support vector machine, and to explore the correlation between the inspection items and the diagnosis results. The experimental results show that the malignant ovarian tumor prediction model constructed by the two machine learning algorithms has high prediction levels, and non-specific inspection items such as red blood cell distribution width and mean platelet volume have strong correlation with the diagnosis results of malignant ovarian tumors.
[1] HUANG H,WU K,CHEN L,et al.Study on the Application of Systemic Inflammation Response Index and Platelet-Lymphocyte Ratio in Ovarian Malignant Tumors[J].International Journal of General Medicine,2021,14:10015-10022.
[2] 王瀚苑，赵之滢，宫婷婷，等.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.
[3] 张桐硕，任鹤菲，曹瑾，等.基于集成机器学习的卵巢癌多检验指标联合诊断模型[J].临床检验杂志，2018,36(12):908-913.
[4] 牟冬梅，任珂.三种数据挖掘算法在电子病历知识发现中的比较[J].现代图书情报技术，2016(6):102-109.
[5] 李博.机器学习实践应用[M].北京：人民邮电出版社，2017.
[6] UNNIKRISHNAN P,KUMAR D K,POOSAPADI ARJUNAN S,et al.Development of Health Parameter Model for Risk Prediction of CVD Using SVM[J].Computational and Mathematical Methods in Medicine,2016,2016:3016245.
[7] 陈敏欣，郜意，康玉，等.人工智能在妇科恶性肿瘤领域应用的研究进展[J].中华妇产科杂志，2022,57(1):72-78.
[8] 刘金花，王洋，赵婧.基于集成学习的疾病预测模型研究[J].微型电脑应用，2021,37(4):91-94.
[9] QIN Y,WANG P,HUANG Z B,et al.The Value of Red Cell Distribution Width in Patients with Ovarian Cancer[J].Medicine,2017,96(17):e6752.
[10] QIN Y Y,WU Y Y,XIAN X Y,et al.Single and Combined Use of Red Cell Distribution Width,Mean Platelet Volume,and Cancer Antigen 125 for Differential Diagnosis of Ovarian Cancer and Benign Ovarian Tumors[J].Journal of Ovarian Research,2018,11(1):10.
[11] 黄海涛，陈姝玉，耿旭，等.2005—2016年中国女性卵巢癌发病及死亡趋势研究[J].中国全科医学，2022,25(8):990-994.
[12] 穆慧娟，于丽娅，礼彦侠，等.2006—2017年辽宁5城市卵巢癌发病和死亡趋势分析[J].中国慢性病预防与控制，2022,30(1):73-77.
[13] LI J,JIAO X D,YUAN Z F,et al.C-reactive Protein and Risk of Ovarian Cancer:A Systematic Review and Meta-analysis[J].Medicine,2017,96(34):e7822.
基本信息:
中图分类号:R737.31;TP181
引用信息:
[1]王莹,顾大勇.基于机器学习的卵巢恶性肿瘤预测模型[J].微型电脑应用,2024,40(04):64-66+71.
基金信息:
深圳市科技计划项目(ZDSYS20210623092001003)
2024-04-20
2024-04-20