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Chapter 8 in Democracy in the era of Artificial Intelligence: Opportunities and Risks
Abstract
Public health governance faces challenges in integrating neonatal monitoring data, detecting respiratory deterioration early, and supporting transparent clinical decision-making. This study proposes a Clinical Decision Support System based on Artificial Intelligence and Internet of Things technologies for monitoring neonatal respiratory disorders in intensive care settings. The study employs a system design research approach involving needs analysis, architecture development, artificial intelligence modelling, and conceptual evaluation. The proposed system integrates medical sensors, real-time data processing, and predictive analytics to support early warning and risk classification. Findings indicate that the model can enhance data integration, improve responsiveness in clinical decisions, and strengthen transparency and accountability in public health governance. The study contributes a practical framework for implementing intelligent neonatal monitoring systems and provides policy implications for future digital health governance.