In this study, we mainly focus on the application of deep learning in the classification of antimicrobial drug using methods and data mining. In the process of text data mining using existing methods of using antimicrobial drugs in disease and electronic medical records, we use the Long Short-Term Memory model (LSTM) based on attention model to train the data of antimicrobial drugs corpus, and express and understand the problems by means of self-learning features, so as to avoid the error of extracting artificial features. The maximum classification accuracy is increased to 89.97% compared with the traditional data mining method. As a result, it provides better antimicrobial treatment plans for patients with different diseases. According to the experimental results, the proposed method can automatically learn and generate treatment knowledge base without the need for manual rules, so as to provide the decision-making support for doctors to treat patients.