Resilient healthcare systems for sustainable development goals (SDGs): A novel framework for generative artificial intelligence

Abstract

The rising frequency of global health emergencies, be they pandemics or natural disasters, reveals grotesque fragilities of the health-care systems in the world, which threatens progress toward United Nations Sustainable Development Goals (SDGs) pertaining to health and wellbeing. This research presents a novel framework based on generative artificial intelligence (AI) that will provide improvements to health-care system resilience, while also promoting progress toward health-related SDGs. We developed a methodology incorporating generative AI models including large language-type models and generative neural networks along with systems analytics, so that simulated crisis scenarios will be created while optimizing resource allocations and informing generally decision-making. To quantify resilience under AI-computerized strategies, complex statistical modeling applied for defining a resilience index, and optimizing certain outcomes. Crisis anticipation, resource supplies efficiency with regard to health systems and capacity for system recovery are all cashed in significantly by virtue of the generative AI framework. Simulated results invariably show that the implementation of AI strategies shorten the time taken for critical health services to be retained by health systems, and the recovery time is shortened when very conventional strategies employed. We discuss how the application of AI-specialized, synthetic data and scenarios provide very much more efficient testing of the performance of putative interventions needed, and also how the questions of data biasness, ethical points, and the final arbiter being human being all need to be effectively considered. This AI methodology has radically reconstructed applications of building up resilience health-care systems. There is a forward-looking approach entailed in this research with regard to action on global health policy and disaster preparedness facility, with practical results.