Titlebook: Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Com; First International Hongen Liao,Simo

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An Approach to Predict Multiple Cardiac Diseasescan be classified into two categories according to morphology and rhythm, four in each group. In this paper, for morphology tasks neural network is applied mainly with input median wave extracted from raw data, while traditional methods are executed and promoted by machine learning to achieve rhythm

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A 12-Lead ECG Arrhythmia Classification Method Based on 1D Densely Connected CNNormal type and eight abnormal types), using a 1D densely connected CNN which is a relatively novel convolutional neural network (CNN) model and shows outstanding performance in the field of pattern recognition. Firstly, noticing that ECG records are one dimensional time series with different noise l

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DUST

Attention-Guided Decoder in Dilated Residual Network for Accurate Aortic Valve Segmentation in 3D CT valve-sparing surgery. However, the very fast flapping speed, ambiguous shapes and extremely thin structures of the aortic valve lead to great difficulties in developing automatic segmentation algorithms. In this paper, we proposed an end-to-end deep learning method to address the problem of segmen

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