Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning

Abstract

To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable selection of antibiotics specifically including reasonable and effective oxygen administration, atomization, sputum discharge treatment, psychotherapy, and rehabilitation training and treatment. Results were indicated, and there were significant differences between the lung function evaluation index and the two groups. Its intelligent monitoring mode was 97.5% and 80.0%, while the red blood cell ratio, arterial oxygen partial pressure (PaO2), pulse blood oxygen saturation (SpO2), arterial carbon dioxide partial pressure (PaCO2), and symptom improvement were better than artificial and were statistically significant ( $P<0.05$ ). Therefore, the training of the anti-inspiratory muscle can effectively improve the lung function and dyspnea symptoms of COPD patients at the stable stage, thus greatly improving their respiratory function and ensuring the quality of life of patients, which is worthy of clinical application.