International Journal of Medicine and Data

The paper deeply explores the complex relationship between maternal physical and psychological indicators and infant behavioral characteristics, and further proposes innovative mathematical modeling methods to predict and analyze these associations. The research method of the paper is rigorous. First, data preprocessing is conducted to ensure the accuracy and usability of the data. Then, through statistical analysis techniques, the intrinsic relationship between maternal health status and infant behavioral characteristics is accurately revealed. In this process, clustering technology is effectively applied to help researchers identify groups with similar characteristics in complex data, further deepening our understanding of the relationship between mothers and infants.This paper successfully constructed an optimization model, which aims to reduce the cost of treating contradictory infant behavior characteristics. This not only provides a new perspective on the issue of infant behavioral characteristics, but also provides economically feasible strategies for achieving a shift towards intermediate and quiet types.

Correlation analysis; K-means clustering; Integer programming model; Euclidean distance