IMPLEMENTATION OF AN AI-BASED CLINICAL DECISION SUPPORT SYSTEM FOR THE SCREENING OF TYPE 2 DIABETES MELLITUS IN PUBLIC HEALTH

• DOI: https://doi.org/10.22533/at.ed.15956326020313

• Palavras-chave: Type 2 diabetes mellitus. Artificial intelligence. Machine learning. Clinical Decision Support System. Public health. Early screening.

• Keywords: Type 2 diabetes mellitus. Artificial intelligence. Machine learning. Clinical Decision Support System. Public health. Early screening.

• Abstract:

  Type 2 diabetes mellitus (T2DM) represents one of the greatest challenges in global public health, characterized by insulin resistance, high mortality rates, and growing prevalence, particularly in middle-income countries. In this context, artificial intelligence (AI) emerges as a strategic tool for early screening and individual risk prediction. This study aims to analyze the implementation of AI-based Clinical Decision Support Systems (CDSS) for T2DM screening in public health programs through a systematic literature review. Results showed that machine learning and deep learning models outperform traditional statistical methods, with accuracy exceeding 91% in some studies. The integration of technologies such as cloud computing, edge computing, and blockchain enhances scalability, operational efficiency, and data security. It is concluded that the adoption of AI-based CDSS in primary health care can represent a significant advancement in service organization, equitable access, and financial sustainability of public health systems.