With the acceleration of population aging, the traditional elderly care model has been difficult to meet the diversified and individualized needs of the elderly, and digital intelligent elderly care has become a hot spot in current research. Based on the digital intelligent community body-nursing integration senior living model, this study analyzes and optimizes senior living services using data mining and intelligent algorithms, specifically including the construction of an evaluation index system and the evaluation and selection of different senior living models using multi-objective optimization algorithms. The research methodology mainly involves the construction and validation of the algorithm model, testing the effectiveness of the algorithm through actual data, and analyzing the application effect of specific elderly care models with case studies. The increase in user satisfaction ratings is also worth noting, with ratings ranging from 4.5 to 5.0, reflecting the recognition and love of elderly people and their families for comprehensive digital services. This research not only provides scientific evaluation tools and decision-making support for the community body-nursing integration elderly care model, but also promotes the practical application of intelligent elderly care services, helping to improve the quality of elderly care services and the living standards of the elderly, which is of great social value and theoretical significance. Through this study, we expect to provide a practical intelligent solution for the senior care industry, so that the senior care service can be more accurate and efficient.

Feng Yang. Algorithm Evaluation and Selection of Digitized Community Physical Care Integration Elderly Care Model. International Journal of Big Data Intelligent Technology (2024), Vol. 5, Issue 1: 70-81. https://doi.org/10.38007/IJBDIT.2024.050109.

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