Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-d convolutional neural networks

HIGHLIGHTS

SUMMARY

Convolutional neural_network (CNN) is one of the main DL architectures for accomplishing medical diagnosis tasks of cancer tumors. Recurrent neural_networks (RNNs) are also widely used as a deep learning model for processing sequential data. "Medical data" and "1D Convolutional Neural_Network", respectively. 1D Convolutional Neural_Network CNN represents an effective tool to extract features and accomplish classification tasks in medicine. To prevent neural_network overfitting, the dropout is applied as a regularization technique for self-modifying the architecture of CNN. The LSTM is one of the most popular architectures of recurrent neural_networks (RNNs) to manipulate data sequentially . . .

 



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