摘要
目的探讨肿瘤标志物人工神经网络模型对结直肠癌的诊断价值。方法对7项肿瘤标志物联合检测,利用人工神经网络(ANN)技术建立结直肠肿瘤标志物智能诊断模型。结果结直肠肿瘤标志物的ANN诊断模型对测试组结直肠癌进行识别的敏感性为0.914,特异性为0.964,准确性为0.939,均显著高于任意单项检验预测结果(P=0.000)。结论与单一肿瘤标志物相比,利用ANN建立的多种血清肿瘤标志物诊断模型能提高诊断大肠癌的敏感性、特异性和准确性,对结直肠癌的早期诊断具有较高价值。
Objective To investigate the value of an artificial neural network （ANN） model based on tumor marker in serum for diagnosing coloreetal carcinoma. Methods A diagnostic model for colorectal carcinoma based on 7 tumor markers which were assayed combinedly was constructed with ANN. Results The sensitivity of the ANN diagnostic model for coloreetal carcinoma was 0. 914, the specificity was 0. 964, and its accuracy was 0. 939. All the above three indexes were higher than that of any single tumor marker （ P =0. 000）. Conclusion Compared with a single tumor marker, the ANN model based on multiple tumor markers in serum can markedly increase the sensitivity, specificity and accuracy for detecting colorectal carcinoma. It has a higher value in early diagnosing eolorectal carcinoma.
出处
《结直肠肛门外科》
2009年第6期380-382,共3页
Journal of Colorectal & Anal Surgery
关键词
人工神经网络
肿瘤标志物
结直肠癌
诊断
Artificial neural network （ANN）
Tumor marker
Colorectal carcinoma
Diagnosis
