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HARNESSING THE POWER OF LANGUAGE MODELS FOR INTELLIGENT DIGITAL
HEALTH SERVICES
1
Garima, Sogani ; Swapnil, Morande ; Shashank, Shah
12
1
1 NITI Aayog, India
2 National Informatics Centre, India
ABSTRACT services hold immense potential to revolutionize healthcare
delivery by providing accessible, affordable, and tailored
This research proposes a novel framework that integrates solutions to individuals' unique health needs. Generative AI
state-of-the-art large language models (LLMs) with curated models, such as OpenAI's GPT series, Google's BERT, and
medical knowledge bases to enable personalized, reliable, others, have demonstrated remarkable capabilities in
and user-centric digital health services. The architecture understanding and generating human-like text, engaging in
combines advanced generative models, retrieval-augmented contextual conversations, and reasoning over complex
generation, and domain adaptation strategies to ensure the information [4]. These models learn from vast amounts of
safety and ethical alignment of AI-driven health data to build rich statistical representations of language,
recommendations. Empirical evaluations, including knowledge, and reasoning patterns. By leveraging these
automated benchmarks and user studies, demonstrate the capabilities, digital health platforms can offer intelligent,
framework's ability to provide accurate, relevant, and interactive, and personalized services that cater to users'
personalized health information that resonates with patients specific health profiles, preferences, and goals [5]. However,
and providers. The results highlight the potential of this realizing the full potential of generative AI in digital health
approach to bridge the gap between general-purpose LLMs also presents significant research challenges [6]. These
and domain-specific healthcare applications. However, the include ensuring AI systems' reliability, safety, and ethical
work also underscores the challenges in responsibly alignment; protecting user privacy and data security;
developing and deploying generative AI for healthcare, such enabling seamless integration with existing healthcare
as safety, robustness, fairness, privacy, and interpretability. infrastructures; and fostering trust and adoption among
The research advocates for multidisciplinary collaboration diverse user populations. Addressing these challenges
to address these challenges and realize the potential of AI in requires multidisciplinary efforts spanning AI, human-
enhancing health and well-being worldwide. By prioritizing computer interaction, health informatics, and social sciences.
patient agency, clinical validity, and ethical practices, this This research paper explores the opportunities, challenges,
work contributes to the growing body of knowledge at the and future directions for leveraging generative AI to enable
intersection of AI and healthcare, laying the foundation for personalized digital health services. It aims to provide a
future research and innovation in personalized, equitable, comprehensive overview of the current state-of-the-art,
and trustworthy AI health services. identify key research gaps, and propose a roadmap for future
work in this important domain. The paper is organized as
Keywords – generative AI, personalized healthcare, follows: Section 2 reviews related literature on AI-driven
knowledge retrieval, language models; ethical AI health services; Section 3 describes our proposed
methodology based on generative AI and knowledge
1. INTRODUCTION retrieval; Section 4 presents result from initial experiments;
Section 5 discusses key findings and their implications; and
The rapid advancement of artificial intelligence (AI) Section 6 concludes with a summary of contributions and
technologies, particularly in the domain of generative AI and future research directions.
large language models (LLMs), has opened up exciting new
possibilities for delivering personalized digital health 2. LITERATURE REVIEW
services [1]. As emphasized by the United Nations'
Sustainable Development Goals (SDGs) and the 2.1 AI in Digital Health Services
International Telecommunication Union's (ITU) vision,
harnessing the power of information and communication The application of AI in healthcare and digital health
technologies (ICTs) can accelerate human progress, bridge services has been an active area of research in recent years
digital divides, and enable sustainable growth and [7]. AI techniques such as machine learning, natural
development for all [2][3]. In this context, AI-driven e-health language processing, computer vision, and robotics are being
978-92-61-39091-4/CFP2268P @ITU 2024 – 115 – Kaleidoscope