Study on early warning treatment of senile depression in community based on artificial intelligence model

Abstract

BackgroundIn recent years, with the acceleration of population aging in China, the number of elderly people with depression is increasing. Artificial intelligence models and data analysis have sound applications in the early warning and treatment of the elderly with depression in the community by finding the elderly with depression timely and carrying out early warning treatment for them.Subjects and Methods50 elderly people with depression, from two communities of equal size, were randomly selected to participate in the experiment. Among them, one community adopts routine management and treatment, and the other community conducts early-warning treatment based on an artificial intelligence model and data analysis. The former and the latter were used as the observation group and the intelligent group respectively. All the elderly were evaluated according to the Geriatric Depression Scale (GDS) before and 6 months after the experiment.ResultsThe GDS scores of the elderly in the observation group and the intelligent group before and after the experiment are shown in Table 1. The GDS scores of the observation group and the intelligent group are close before and after the experiment from Table 1. Six months after the experiment, the GDS scores of the intelligent group are significantly lower than that of the observation group. In this experiment, P < 0.0 indicates that the difference is statistically significant.Table 1.GDS score results of the two groups of elderly before and after the experimentGroupProjectGDS score before the experimentGDS score after theexperimentObservation groupScore17.18±1.4514.71±1.13t0.1251.234P0.0340.039Intelligent groupScore16.31±1.2710..28±0.97t0.2431.314P0.0190.028ConclusionsAccording to statistics, the incidence rate of depression in the elderly can reach 10%, so it is necessary to strengthen the early warning and treatment of depression symptoms in the elderly. The artificial intelligence model and data analysis can help find the depressive symptoms of the elderly in the community as early as possible, and help take measures to carry out early warning treatment, thereby improving the depressive situation.AcknowledgementThe research is supported by: Provincial key platforms and major scientific research projects of Guangdong universities “Building an intelligent community public welfare platform based on blockchain (No. 2021ZDZX3004)”.