Xu Jie, Gao Hong, Sun Qi

Hainan Vocational University of Science and Technology

Abstract：

With the rapid advancement of Artificial Intelligence (AI) technologies, the field of medical imaging diagnosis is undergoing unprecedented transformation. Children, as a unique population, require early disease identification that is critical to their growth and overall health. This paper explores the application of AI-based imaging diagnostic technologies in the early identification of pediatric diseases. It analyzes the core algorithms and mechanisms of AI in image recognition and investigates its clinical applications in assisting the diagnosis of common conditions such as brain development disorders, pneumonia, and congenital heart disease. The paper highlights existing issues such as data privacy, algorithmic bias, and lack of model interpretability, and anticipates future developments in precision medicine, cross-modal integration, and personalized healthcare. The findings indicate that AI imaging diagnosis technologies significantly enhance the efficiency and accuracy of early screening for pediatric diseases, offering great potential for clinical adoption and optimization

Key Words：

artificial intelligence; pediatric imaging diagnosis; early disease identification; deep learning; medical imaging