Diabetes ICU patient death risk prediction method based on artificial intelligence

Abstract

The invention discloses a diabetic ICU patient death risk prediction method based on artificial intelligence. The method comprises the following steps: S1, collecting ICU data of a diabetic ICU patient according to a set standard; s2, importing the collected ICU data into a database, and taking out vital sign data of a diabetic ICU patient; s3, deleting data which do not meet the specification in the acquired ICU data and the vital sign data; s4, constructing a prediction model based on a logistic regression algorithm, a prediction model based on a decision tree algorithm, a prediction model based on a random forest algorithm and a model based on hybrid bidirectional LSTM; s5, inputting the ICU data and the vital sign data processed in the step S3 into the model in the step S4 for model training and iterative training, and selecting an optimal model; and S6, inputting the basic information of the diabetic ICU patient and the vital sign data of the patient into the optimal model to predict the death risk. According to the invention, an early warning effect can be achieved, so that the treatment condition of a diabetic ICU patient is improved.

Description

technical field [0001] The invention relates to the technical field of medicine and computer application, and more particularly, to a method for predicting the death risk of diabetic ICU patients based on artificial intelligence. Background technique [0002] Diabetes Mellitus (DM) is mainly characterized by maintaining high blood sugar for a long time. Its etiology is more complex and is usually not caused by a single disease. cure. With rapid urbanization, economic development and changes in sedentary lifestyles, diabetes has gone from a rare disease to an epidemic, with the prevalence of diabetes soaring from 0.67% in 1980 to 9.3% in 2019. The increasing prevalence is a major health problem facing human beings. [0003] Intensive care unit (ICU) patients have complex etiologies and rapid disease progression. Doctors take timely and effective treatment to play an important role in the prognosis of patients. However, only relying on doctors' clinical experience to make ju...

AI Technical Summary

Problems solved by technology

[0003] The etiology of patients in the intensive care unit (ICU) is complex and the disease develops rapidly. Doctors' timely and effective treatment plays an important role in the prognosis of patients, but the reliability is not very high if only relying on the doctor's clinical experience to judge

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