Children pneumonia auxiliary diagnosis model and training method thereof
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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
Active Publication Date: 2021-08-10
HUAQIAO UNIVERSITY
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Problems solved by technology
However, the interpretation results of the same chest X-ray medical image at different time points or by different doctors are highly inconsistent and have great observer differences
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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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Abstract
The invention provides a child pneumonia auxiliary diagnosis model and a training method thereof; the training method comprises the steps: obtaining a medical image of a child pneumonia patient and a corresponding medical diagnosis statement, enabling the medical image to serve as a training image set, and enabling the medical diagnosis statement to serve as a training statement; extracting an image depth feature vector from the image training set data through a CNN neural network to obtain a depth feature image set, and performing word vector training on the training statement through a word2vec model to obtain a depth feature vector word set; and carrying out feature fusion on the deep feature image set and the deep feature vector word set, and then carrying out training through an LSTM neural network so as to obtain a trained child pneumonia auxiliary diagnosis model. According to the method, the existing medical image of the child pneumonia patient and the corresponding medical diagnosis statement are trained, and the model obtained through training serves as a tool for a doctor to learn diagnosis or provides effective reference opinions for clinical diagnosis of the doctor.
Description
technical field [0001] The invention relates to the technical field of medical computers, in particular to an auxiliary diagnosis model of pneumonia in children and a training method thereof. Background technique [0002] Pneumonia is the leading infectious cause of death in children under 5 years of age. It kills nearly 2,500 children every day, accounting for about 16 percent of the 5.6 million deaths of children under five in 2016, according to UNICEF. Pneumonia in children is a common disease in infants and young children. It is more common in winter and spring in northern my country, and it is a common cause of infant death. Pneumonia is lung inflammation caused by pathogen infection or inhalation of amniotic fluid and oil, and allergic reactions. The main clinical manifestations are fever, cough, shortness of breath, dyspnea, and lung rales. The examination of pneumonia in children includes routine blood examination, C-reactive protein test, etiological examination, ...
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