Children pneumonia auxiliary diagnosis model and training method thereof
A technology for auxiliary diagnosis and pneumonia, which is applied in the field of medical computers, can solve the problem of high inconsistency of interpretation results, achieve the effect of solving long-term dependence problems and speeding up the convergence speed
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Embodiment 1
[0023] This embodiment provides a child pneumonia auxiliary diagnosis model, such as figure 1 As shown, it is obtained through the following steps of training:
[0024] S1. Obtain medical images of children with pneumonia (i.e. chest X-rays of children under 5 years old), and corresponding medical diagnosis sentences, the medical images are used as a training image set, and the medical diagnosis sentences are used as training sentences;
[0025] S2. Extract image depth feature vectors from the image training set data through the CNN neural network, retain effective information through deep extraction of spatial features, obtain a depth feature atlas, and perform word vector training on the training sentences through the word2vec model to obtain Deep feature vector word set;
[0026] S3. Perform feature fusion on the deep feature atlas and the deep feature vector word set to obtain a fusion feature set;
[0027] S4. The fused feature set is trained through the LSTM neural net...
Embodiment 2
[0059] In this embodiment, a training method of an auxiliary diagnosis model for children's pneumonia is provided, such as figure 1 shown, including the following steps:
[0060] S1. Obtain medical images of children with pneumonia and corresponding medical diagnosis sentences, the medical images are used as a training image set, and the medical diagnosis sentences are used as training sentences;
[0061] S2. Extract image depth feature vectors from the image training set data through a CNN neural network to obtain a depth feature atlas, and perform word vector training on the training sentences through a word2vec model to obtain a depth feature vector word set;
[0062] S3. Perform feature fusion on the deep feature atlas and the deep feature vector word set to obtain a fusion feature set;
[0063] S4. The fused feature set is trained through the LSTM neural network to obtain a well-trained child pneumonia auxiliary diagnosis model.
[0064] Wherein, as a better or more spe...
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