Deployment of AI Models and a TDA Mapper Algorithm to Enhance Clinical Decision-Making

This research presents a novel Clinical Decision Support System (CDSS) that integrates advanced AI technologies, including a hybrid model for COVID-19 diagnosis and a custom GPT Assistant, into a scalable, real-world tool for resource-limited healthcare settings. The CDSS enhances the quality of care by providing accurate, timely diagnostics and decision support, while also improving response efficiency through real-time monitoring and predictive analytics. The system’s adaptability, supported by open-source platforms like R Shiny, and its potential for wide adoption, particularly after a planned pilot and impact evaluation, highlight its significance in advancing healthcare delivery where resources are scarce. The deployment of this AI-driven CDSS has the potential to transform clinical decision-making, improve healthcare delivery, and enhance the overall response to public health emergencies. The structured pilot and impact evaluation will provide critical insights into the system’s effectiveness in real-world settings, paving the way for broader adoption and sustained improvements in healthcare quality and efficiency.