Revolutionizing Healthcare

Abstract

In the evolving realm of healthcare, there is a notable shift from traditional methods in generalized systems toward personalized approaches. This chapter explores the integration of machine learning and generative artificial intelligence (AI), particularly large language models (LLMs), for developing an advanced Q&A system customized for health inquiries. Unlike conventional methods, the proposed approach advocates for a revolutionary change in healthcare delivery, redefining normative systems with customized AI techniques. The objective is to address the specific needs of doctors, policymakers, governments, and healthcare systems. This initiative involves fine-tuning LLMs using a curated in-house dataset, ensuring relevance and accuracy in the healthcare domain. This chapter focuses on developing a personalized chatbot system as a responsive and accessible medium for healthcare information. This tailored solution is poised to benefit stakeholders, including hospitals, governments, and telemedicine providers, especially in remote areas with limited healthcare infrastructure. The system aims to bridge gaps by offering real-time, accurate, and personalized responses to health queries. The urgency of adopting customized AI in healthcare is underscored by the need for a swift approach to reach a large society efficiently. Leveraging generative AI and machine learning, the chapter emphasizes the potential of the proposed solution to revolutionize healthcare services, providing timely and accurate information dissemination. The implications extend beyond conventional healthcare settings, addressing healthcare disparities in remote regions where telemedicine is crucial. This chapter offers valuable insights into the development and potential impact of a personalized chatbot system, signaling a transformative era in healthcare information dissemination.

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