| 基于RBF神经网络的医院科技影响力评价模型构建 |
| 投稿时间：2016-02-28 点此下载全文 |
| 引用本文：安新颖,代涛,钱庆.基于RBF神经网络的医院科技影响力评价模型构建[J].医学信息学杂志,2016,37(3):8-12 |
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| 基金项目:中国医学科学院医学信息研究所中央公益性基本科研业务课题"中国医院科技影响力评价的关键问题研究"(项目编号:15R011)。 |
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| 中文摘要:在文献调研的基础上基于德尔菲法建立医院科技影响力评价指标体系,根据专家经验和知识对60家医院的科技影响力进行排名。采用径向基函数神经网络方法,将50个医院作为训练样本,10个医院作为测试样本,构建出一套基于径向基函数的医院科技影响力的评价模型,实验结果表明该评价模型较好地拟合了专家的思维,可以使医院科技影响力评价真实有效。 |
| 中文关键词:医院科技影响力 径向基函数神经网络 评价 |
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| Building a Sci-tech Influence Evaluation Model for Hospitals Based on RBF Neural Network |
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| Abstract:Based on literature research, the paper builds a sci-tech influence evaluation index system for hospitals with the Delphi method and ranks the sci-tech influence of 60 hospitals in terms of expertise. By using radial basis function neural network and taking 50 hospitals as training samples and 10 hospitals as test samples, it builds a sci-tech influence evaluation model for the hospitals based on the radial basis function. As indicated by experimental results, this evaluation model fits thoughts of experts well and evaluates the sci-tech influence of hospitals truly and effectively. |
| keywords:Hospital's sci-tech influence Radial basis function neural network Evaluation |
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