ABSTRACT The triple test is a screening test (blood test) used to calculate the probability of a pregnant woman having a fetus that has a chromosomal abnormality like Down Syndrome (DS). AFP (Alpha-Fetoprotein), hCG (Human Chorionic Gonadotropin), and uE3 (Unconjugated Estriol) values in the blood sample of pregnant women are computed and compared with the similar real records where the outputs (healthy fetus or a fetus with DS) are actually known. The likelihood of the indicators is used to calculate the probability of having a fetus with chromosomal abnormality like DS. However, high false positive rate of the triple test has been a problematic issue. One of the reasons of the high false positives is the differences in the norm values of indicators for the pregnant women from different geographical regions of a country. We use 81 patient records retrieved from Şahinbey Training and Research Hospital of Gaziantep University; Turkey. In our study, nine different classification algorithms were trained based on triple test indicators. Multilayer perceptron outperformed with 94.24% detection rate and 13% false positive rate. The multilayer perceptron can predict the outcome of triple test with a high level of accuracy and fewer patients are suggested for amniocentesis. This study is the first study using the MLP model for Turkish triple test data. Regional MLP models can eliminate the bias due to local biological differences.

中文翻译：

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预测胎儿唐氏综合症的分类模型——来自土耳其的研究

摘要 三重测试是一种筛查测试（血液测试），用于计算孕妇的胎儿患有唐氏综合症 (DS) 等染色体异常的可能性。计算孕妇血液样本中的 AFP（甲胎蛋白）、hCG（人绒毛膜促性腺激素）和 uE3（未结合雌三醇）值，并与类似的真实记录进行比较，其中输出（健康胎儿或患有 DS 的胎儿）为其实知道。指标的似然性用于计算胎儿出现DS等染色体异常的概率。然而，三重测试的高误报率一直是一个问题。误报率高的原因之一是一个国家不同地理区域的孕妇指标的常模值存在差异。我们使用从加济安泰普大学 Şahinbey Training and Research Hospital 检索的 81 份患者记录；火鸡。在我们的研究中，基于三重测试指标训练了九种不同的分类算法。多层感知器以 94.24% 的检测率和 13% 的误报率表现出色。多层感知器可以准确预测三联检测的结果，建议进行羊膜穿刺术的患者较少。本研究是首次将 MLP 模型用于土耳其语三重测试数据的研究。区域 MLP 模型可以消除由于局部生物差异引起的偏差。24% 的检测率和 13% 的误报率。多层感知器可以准确预测三联检测的结果，建议进行羊膜穿刺术的患者较少。本研究是首次将 MLP 模型用于土耳其语三重测试数据的研究。区域 MLP 模型可以消除由于局部生物差异引起的偏差。24% 的检测率和 13% 的误报率。多层感知器可以准确预测三联检测的结果，建议进行羊膜穿刺术的患者较少。本研究是首次将 MLP 模型用于土耳其语三重测试数据的研究。区域 MLP 模型可以消除由于局部生物差异引起的偏差。