Enhancing Public Welfare Functions with Deep Learning Technology: A Quantitative Analysis of Strengthening Citizen Rights Protection in China

Abstract

The rapid advancement of deep learning (DL) technology has profoundly impacted numerous sectors, particularly public welfare services, which encompass healthcare, social security, and legal rights protection. In China, where a vast population creates challenges in resource allocation and equitable service distribution, the integration of DL technologies offers promising solutions to enhance efficiency, accuracy, and fairness in public welfare functions. This paper explores how DL can be applied to improve these functions, with a specific focus on enhancing the protection of citizen rights. Through case studies and quantitative data analysis, this research examines how DL technologies can be effectively deployed in the healthcare, social security, and legal sectors, providing a roadmap for modernizing public services and ensuring that citizen rights are safeguarded more comprehensively. Five key references are used to support the analysis of DL’s role in transforming these critical areas of governance, aiming to present practical and actionable insights for policymakers and technology developers.