| 基于BP神经网络的食管鳞癌预后预测模型 |
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| 引用本文： | 刘怡文,杨洪,张灏,周福有,杨海军,孔金玉,孙蔚,原翔,高社干. 基于BP神经网络的食管鳞癌预后预测模型[J]. 食管疾病, 2021, 3(1) |
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| 作者姓名： | 刘怡文 杨洪 张灏 周福有 杨海军 孔金玉 孙蔚 原翔 高社干 |
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| 作者单位： | 河南科技大学信息工程学院,河南洛阳,471023;河南科技大学临床医学院,河南科技大学第一附属医院,肿瘤医院,河南省肿瘤表观遗传重点实验室,中国洛阳,471003;河南科技大学体育学院,中国洛阳,471003;暨南大学医学院肿瘤精准医学与病理研究所,广东广州,510632;河南省安阳市肿瘤医院,河南安阳,455000;河南科技大学临床医学院,河南科技大学第一附属医院,肿瘤医院,河南省肿瘤表观遗传重点实验室,中国洛阳,471003 |
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| 基金项目： | 国家自然科学基金(81702820);河南省科技攻关项目(202102310321,202102310129,212102310670);河南省医学科技攻关项目(2018020273);洛阳市科技计划医疗卫生项目(1813003A)。 |
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| 摘 要： | 目的基于BP神经网络建立食管鳞癌临床辅助诊断模型。方法对食管鳞癌患者的临床信息进行结构化处理,采用BP神经网络建立一种检测模型,对食管鳞癌患者的预后进行预测。结果建立了食管鳞癌患者的预后预测模型,通过测试验证了该模型的可行性。结论基于BP神经网络建立的食管鳞癌患者预后预测模型对临床治疗有参考价值。
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| 关 键 词： | 人工智能 BP神经网络 食管鳞癌 预后 |
Application of BP Neural Network in Clinical Diagnosis of Esophageal Squamous Cell Carcinoma |
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| LIU Yi-wen,YANG Hong,ZHANG Hao,ZHOU Fu-you,YANG Hai-jun,KONG Jin-yu,SUN Wei,YUAN Xiang,GAO She-gan. Application of BP Neural Network in Clinical Diagnosis of Esophageal Squamous Cell Carcinoma[J]. Journal of Esophageal Diseases, 2021, 3(1) |
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| Authors: | LIU Yi-wen YANG Hong ZHANG Hao ZHOU Fu-you YANG Hai-jun KONG Jin-yu SUN Wei YUAN Xiang GAO She-gan |
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| Affiliation: | (School of Information Engineering,Henan University of Science and Technology,Luoyang,China,471023;Henan Key Laboratory of Cancer Epigenetics,Cancer Hospital,The First Affiliated Hospital,and College of Clinical Medicine of Henan University of Science and Technology,Luoyang,China,471003;School of PE.Henan University of Science and Technology,Luoyang,China,471003;Institute of OncologyPrecision Medicine and Pathology,Jinan University Medical College,Guangzhou,China,510632;Anyang Tumor Hospital,Anyang,China,455000) |
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| Abstract: | Objective To establish a clinical assistant diagnosis model for esophageal squamous cell carcinoma based on BP neural network.Methods The clinical information of esophageal squamous cell carcinoma patients was structured and a detection model was established by BP neural network to predict the prognosis of esophageal squamous cell carcinoma patients.Results The prognosis prediction model of esophageal squamous cell carcinoma patients was established,and the feasibility of the model was verified by testing.Conclusion The prognostic model of esophageal squamous cell carcinoma patients based on BP neural network has important reference value for clinical treatment. |
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| Keywords: | artificial intelligence BP neural network esophageal squamous cell carcinoma prognosis |
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