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- W3150653637 abstract "瞄准：在在衰退身体胃炎病人预言甲状腺疾病的存在调查人工的神经网络的角色。方法：253 个衰退身体胃炎病人的 29 个输入变量的数据集用一个数据优化过程被用于人工的神经网络(ANN )( 标准 ANN， T&T-IS 协议，扭曲协议) 。目标变量是甲状腺 disease.RESULTS 的存在：标准 ANN 在与甲状腺疾病认出衰退身体胃炎病人与 69% 的敏感和 59.8% 的特性获得了 64.4% 的吝啬的精确性。优化过程(T&T-IS 和扭曲协议) 改进了产出吝啬的精确性，敏感和特性的识别任务的表演 74.7% 和 75.8% ， 78.8% 和 81.8% ，和 70.5% 和 69.9% 分别地。TWIST 协议的敏感的增加与 T&T-IS 相比是统计上重要的。结论：这研究建议人工的神经网络可以为为 harbouring 在风险识别 ABG 病人作为一个潜在的临床的决定支持工具被考虑要求他们的甲状腺地位的诊断病情的检查的未知甲状腺疾病和 thus。" @default.
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- W3150653637 date "2008-01-01" @default.
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- W3150653637 title "Artificial neural networks in the recognition of the presence of thyroid disease in patients with atrophic body gastritis" @default.
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