Description: 摘要:心电图ST段对心脏疾病的诊断具有重要意义。在正确读取采集于郑州大学一附院的运动心电图数据基础上,利用小波变换更准确地确定其ST段的起始和终止位置,初步探讨了BP神经网络用于心电图ST段识别的方法,并用此方法识别出心电图ST段的三种类型—正常、水平压低和抬高。实验结果较好。
-Abstract: ECG ST segment on the diagnosis of heart disease is important. Collected in the correct reading of the first affiliated hospital of Zhengzhou University in exercise ECG data based on the use of wavelet transform to more accurately determine the ST segment of the start and end position, discussed the BP neural network for ECG ST-recognition method, and use this method to identify three types of ECG ST segment- the normal, the level of depression and elevation. Experimental results are good. Platform: |
Size: 97280 |
Author:Lily |
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Description: 自己2011年12月的神经网络作业，利用神经网络训练：
自组织竞争网络在模式分类中的应用
—患者的某病的发病预测-December 2011, the neural network operation, the use of neural network training: self-organizing competitive network for pattern classification- in patients with the incidence of a disease forecasting Platform: |
Size: 20480 |
Author:稂龙亚 |
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Description: Diabetic retinopathy contributes to serious health problem in many parts of the world. With the motivation of the needs of the medical community system for early screening of diabetics and other diseases, a computer aided diagnosis system is proposed. This work is aimed to develop an automated system to analyze the retinal images for important features of diabetic retinopathy using image processing techniques and an image classifier based on artificial neural network which classify the images according to the disease conditions.-Diabetic retinopathy contributes to serious health problem in many parts of the world. With the motivation of the needs of the medical community system for early screening of diabetics and other diseases, a computer aided diagnosis system is proposed. This work is aimed to develop an automated system to analyze the retinal images for important features of diabetic retinopathy using image processing techniques and an image classifier based on artificial neural network which classify the images according to the disease conditions. Platform: |
Size: 1200128 |
Author:arun |
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Description: The basic hypothesis underlying this algorithm is that to apply Convolution Neural Network algorithm (CEA) effectively to detect the Alzheimer Disease Platform: |
Size: 1024 |
Author:Vinod Kumar |
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Description: The basic hypothesis underlying this algorithm is that to apply Convolution Neural Network algorithm (CEA) effectively to detect the Alzheimer Disease Platform: |
Size: 2048 |
Author:Vinod Kumar |
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Description: classify data (heart disease) by using artificial neural network (ANN) to 2 class and 5 class Platform: |
Size: 44032 |
Author:WENG0125 |
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Search - neural network disease