Pediatric pneumonia auxiliary diagnosis model training method and model obtained through training

The invention provides a pediatric pneumonia auxiliary diagnosis model training method and a model obtained through training, and the training method comprises the steps: obtaining a medical image of a pediatric pneumonia patient and a corresponding medical diagnosis statement, processing the medical image into a uniform specification m * m pixel size, and then forming a training set; extracting an LBP feature map set, a multi-scale feature map set and a multi-level feature map set from the training set; respectively carrying out attention processing by adopting an attention module and then carrying out feature fusion to obtain a new feature map set; and inputting the obtained feature map set into a classifier for classification to obtain a trained model. According to the method, the medical image of the existing pediatric pneumonia patient is 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