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1.牡丹江医学院第一临床医学院,黑龙江牡丹江 157011
2.牡丹江医学院附属红旗医院,黑龙江牡丹江 157011
3.牡丹江医学院医学影像学院,黑龙江牡丹江 157011
沈翔 (2001—),男,研究生在读,研究方向:临床医学。
孙悦 (1992—),女,初级职称,研究方向:人工智能。
郭金兴 (1984—),女,中级职称,研究方向:人工智能。
王振 (2000—),男,研究生在读,研究方向:医学人工智能。
陈广新 (1978—),男,中级职称,研究方向:医学图像处理。
韩雪山
纸质出版日期:2023-10-30
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沈翔, 孙悦, 郭金兴, 等. 基于PSO-BP神经网络的儿童骨髓移植生存预测研究[J]. 新一代信息技术, 2023, 6(20): 17-21
SHEN Xiang, SUN Yue, GUO Jin-xing, et al. Research on Bone Marrow Transplantation Survival Prediction Based on Particle Swarm Optimized BP Neural Network[J]. New Generation of Information Technology, 2023, 6(20): 17-21
沈翔, 孙悦, 郭金兴, 等. 基于PSO-BP神经网络的儿童骨髓移植生存预测研究[J]. 新一代信息技术, 2023, 6(20): 17-21 DOI: 10.3969/j.issn.2096-6091.2023.20.003.
SHEN Xiang, SUN Yue, GUO Jin-xing, et al. Research on Bone Marrow Transplantation Survival Prediction Based on Particle Swarm Optimized BP Neural Network[J]. New Generation of Information Technology, 2023, 6(20): 17-21 DOI: 10.3969/j.issn.2096-6091.2023.20.003.
构建一种儿科患者骨髓移植生存预测模型。利用Kaggle儿童骨髓移植数据集基于PSO-BP(Particle Swarm Optimized Back Propagation)神经网络构建预测模型。研究结果表明,预测模型AUC(Area Under the Curve)值为0.98,算法模型表现优秀,特征重要性分析揭示了生存时间、复发和每公斤受体体重的CD34+细胞剂量等特征是骨髓移植儿童患者的生存预后最重要的影响因素。
To construct a survival prediction model for pediatric patients undergoing bone marrow transplantation. A prediction model was built based on the Kaggle dataset for children's bone marrow transplantation using a PSO-BP (Particle Swarm Optimized Back Propagation) neural network. The prediction model has an AUC (Area Under the Curve) value of 0.98
indicating excellent performance of the algorithm model. Feature importance analysis revealed that survival time
recurrence
and CD34+ cell dose per kilogram of recipient weight are the most important factors affecting the survival prognosis of pediatric bone marrow transplantation patients.
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刘金平 , 吴娟娟 , 张荣 , 等 . 基于结构重参数化与多尺度深度监督的COVID-19胸部CT图像自动分割 [J ] . 电子学报 , 2023 , 51 ( 5 ): 1163 - 1171 .
谢娟英 , 张凯云 . SOSNet: 一种非对称编码器-解码器结构的非小细胞肺癌CT图像分割模型 [J ] . 电子学报 , 2024 , 52 ( 3 ): 824 - 837 .
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