Abstract
Over the past decade the global human population has grown exponentially. Along with the population the number of healthcare requests over the past decade has also increased a lot and overwhelming the healthcare providers with surplus of requests that they cannot serve. According to the many healthcare providers, doctors & healthcare experts, a good amount of these requests are related to very mild health problems such as common cold, dry eyes, low fevers, sour throat, fatigue etc. Which can be easily diagnosed, treated and prevented with the help of a well-designed Intelligent AI system. This conversation AI agent can not only decrease the healthcare requests for medical providers, but can also be a very powerful tool in the hands of people who are living in remote, secluded areas allowing them to quickly find resources to cure their mild healthcare conditions and also instruct them to see a doctor if the health condition diagnosis is beyond the capability for the bot. This undying requirement allowed us to analyse and build a more scalable, intelligent AI system which is internally built on top of multiple individual agents that are separated based on their concerns and responsibilities. Allowing the AI conversation agent to leverage the pieces of it as needed and can scale in the areas it needs to scale. This research pioneers a novel multi-agent AI conversation agent in a big step towards building scalable, efficient, human trained intelligent healthcare systems improving availability, accessibility, and cognitive well-being of an individual. This work establishes a new paradigm for equitable AI-driven healthcare, with implications for national health infrastructure reform.
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