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SVM Based Predictive Model for SGA Detection

机译:基于SGA检测的SVM预测模型

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摘要

The medical diagnosis process can be interpreted as a decision making process, which doctors determine whether a person is suffering from a disease based on the medical examination. This process can also be computerized in order to present medical diagnostic procedures in an accurate, objective, rational, and fast way. This paper presents a detection model for small for gestational age (SGA) based on support vector machine (SVM). For this purpose, a dataset was adopted from pregnancy eugenic investigation to train the classification model. Then empirical experiments were conducted for SGA detection. The results indicate that support vector machine is considerably effective to detect SGA to help doctors make the final diagnosis.
机译:医学诊断过程可以被解释为决策过程,医生确定一个人是否患有基于体检的疾病。该过程也可以通过计算机化,以便以准确,客观,理性和快速的方式呈现医疗诊断程序。本文介绍了基于支持向量机(SVM)的胎龄(SGA)小的检测模型。为此目的,采用数据集从怀孕的优质考察中采用,以培训分类模型。然后进行经验实验进行SGA检测。结果表明,支持向量机可有效地检测SGA以帮助医生进行最终诊断。

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