基于人工神经网络的心脏病诊断预测工具

Rommel M. Lim, Francisco Emmanuel T. Munsayac, N. Bugtai, R. Baldovino
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引用次数: 1

摘要

随着人工神经网络(artificial neural networks, ANN)应用的不断增加,它已经通过能够支持执行医疗决策或临床诊断而进入医疗领域。更具体地说,人工神经网络的使用在诊断菲律宾常见疾病(如心脏病)方面显示出更有希望的结果。在本研究中,利用人工神经网络来评估患者的病情,并提供有效和准确的预测。为了实现这一目标,需要收集和组织患者的数据,包括血糖、胆固醇、年龄等。然后,使用人工神经网络对所述数据进行训练。从这项研究中,一个准确的预测方法或程序可以作为一个预警系统,可以避免昂贵的医疗检查,许多或一些菲律宾人无法立即负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Predictive Tool for Heart Disease Diagnosis using Artificial Neural Network
With the continuously growing number of applications of artificial neural networks (ANN), it has reached the medical field by being able to support in performing medical decisions or clinical diagnosis. More particularly, the use of ANN has shown more promising results in the diagnosis of common illnesses in the Philippines such as the heart disease. In this study, ANN was utilized in order to assessed a condition of a patient and provide an effective and accurate prediction. To attain this objective, it is needed to gather and organize the patient’s data that includes the blood sugar, cholesterol, age, etc. Then, the said data was trained using ANN. From this study, an accurate prediction method or procedure could serve as a warning system that could avoid the expensive medical check-ups that many or some Filipinos could not afford in an instant.
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