Construction of community health care integration using artificial intelligence models

The primary focus of this research is on the integration model of community health care for the elderly floating population. It combines service design theory and incorporates an integration strategy and construction approach for providing health services to the floating elderly population. A stacking optimization model is employed to summarize correlation degrees and calculate importance scores for their needs. Based on this scoring system, a community health care model is constructed that enables intelligent cooperation and human–computer interaction specifically tailored to meet the needs of the mobile elderly population. Additionally, a mobile terminal is designed based on this model. Experimental results demonstrate that our proposed model assigns high-importance scores (ranging from 4.48 to 5.00) to community health care indicators for the elderly floating population, accounting for 52.17–100% of their overall score distribution range. Secondary indicators also receive significant importance scores ranging from 4.43 to 5.00, representing between 47.83 and 100% of their full score range; while third-level indicators have importance scores ranging from 3.87 to 5.00, accounting for between 21.74 and 100% of their full score range, respectively. The Kaiser–Meyer–Olkin (KMO) value obtained in our study was found to be satisfactory at a level of 0.93 indicating good sampling adequacy.