Application of Deep Neural Network Model Combined with Factor Analysis in Clinical Nursing Effect Analysis of Blood Glucose Level in Elderly Type 2 Diabetic Patients

Abstract

In order to explore the clinical nursing effect of blood glucose level in elderly type 2 diabetic patients, this paper combines the deep neural network model and factor analysis from the perspective of multifactor analysis to construct a multifactor analysis model for the clinical nursing effect of blood glucose levels in elderly type 2 diabetic patients. Moreover, this paper analyzes the effects through experimental methods, collects cases through hospitals, and formulates research methods and related standards based on nursing research needs. In addition, this paper uses statistical methods to perform data processing, uses factor analysis to screen critical factors, and uses deep neural networks to process nursing data. The statistical results of the experimental research show that the deep neural network model combined with factor analysis can play a certain role in the clinical nursing effect. Thus, the blood glucose level analysis in elderly type 2 diabetic patients can provide a reference direction for the clinical care of blood glucose levels in elderly type 2 diabetic patients.