基于CNN处理疾病数据的技术对疾病预测研究

为了使患者对自身的情况更加了解,医生可以更准确地对疾病进行诊断,目前已经出现了一些将计算机技术用于医疗诊断的研究。但是目前存在的技术在处理疾病诊断的过程中存在电脑处理数据多,维度大,超负荷等缺点。基于这种情况,本文提出了将卷积神经网络(Convolutional Neural Network,CNN)用于处理疾病数据的技术,神经网络对于高维度的数据处理有着无可比拟的优势。CNN网络可以降低数据过拟合现象的发生,可以极大地缓解目前技术存在的问题。这项技术对于患者和医生都有着积极的意义。

Research on Disease Prediction Based on CNN Processing Disease Data

In order to enable patients to better understand their own conditions,and doctors to diagnose the disease more accurately,there have been some studies using computer technology for medical diagnosis.However,the existing technologies have the disadvantages of having more data processed by the computer,large dimensions,and overload in the process of disease diagnosis.Based on this situation,this paper proposes the technology of using Convolutional Neural Network(CNN)to process disease data.Neural networks have incomparable advantages for high-dimensional data processing.The CNN network can reduce the occurrence of data overfitting,which can greatly alleviate the problems of the current technology.This technology has positive implications for both patients and doctors.