Abstract

In an age marked by overwhelming information and a rapidly aging global population, the need for accessible, comprehensible health information has never been more urgent. Although evidence-based health guidelines play a crucial role in supporting informed medical decision-making, their dense medical language and structural complexity often render them inaccessible to lay audiences. This study investigates the transformative role of Artificial Intelligence (AI) in enabling medical libraries to serve as dynamic platforms for promoting the accessible reading of such guidelines, thereby advancing public health literacy and equity.

A dual challenge emerges: on one hand, the expanding volume and sophistication of clinical guidelines; on the other, the unmet needs of vulnerable populations—such as the visually and hearing impaired, those with cognitive disabilities, low literacy skills, and the elderly—who often face significant barriers to comprehension. Conventional dissemination strategies fall short in bridging these gaps. While numerous countries have made progress in producing high-quality evidence-based guidelines, effective and inclusive public dissemination, particularly for non-medical audiences, remains insufficient. With their deep expertise in information access, educational outreach, and user-centered services, medical libraries are uniquely positioned to address this shortfall. AI technologies now offer a powerful means to extend their reach and impact.

This paper synthesizes current international and domestic developments in the promotion of accessible health guidelines. Globally, AI has demonstrated its potential through tools such as computer vision for environmental navigation and real-time speech recognition for communication. Specific to health, initiatives like the WHO’s multilingual digital health assistant and large language models have shown promise in simplifying complex medical texts. In China, policy frameworks supporting accessibility and AI-enabled assistive tools have evolved rapidly; however, a significant gap persists in the intelligent transformation of clinical guidelines into accessible, user-friendly formats.

To bridge this gap, we propose a comprehensive framework for AI-integrated services within medical libraries aimed at creating a multi-modal, inclusive reading experience for health guidelines. The framework encompasses four key strategies. First, AI-driven content simplification and summarization will employ natural language processing and large language models to produce plain-language explanations, concise digests, and multimedia outputs including audio, visual, and sign-language formats. Second, multi-modal presentation tools—such as text-to-speech engines, speech recognition systems, and image-to-text converters—will enable flexible, sensory-adaptive access to information. Third, intelligent recommendation engines and conversational agents will utilize user profiling to deliver personalized content and responsive health information support. Finally, the model underscores the indispensable role of human-AI collaboration: medical librarians and healthcare professionals must actively curate, verify, and refine AI-generated content to ensure scientific integrity and practical usability, supported by iterative feedback loops.

By transforming complex, text-heavy medical information into accessible, engaging formats, AI-augmented medical libraries can substantially elevate public health literacy. This model supports self-directed, informed health choices and helps close persistent information gaps among underserved populations. More broadly, it offers a replicable, forward-looking strategy that aligns with global health equity goals and national initiatives such as the "Healthy China 2030" plan. The findings lay critical groundwork for integrating emerging AI capabilities into the next generation of inclusive health information services.

Keywords

artificial intelligence, medical libraries, evidence-based health guidelines, health equity

Date of this Version

11-2025

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AI Empowerment of Medical Libraries for Promoting Accessible Reading of Evidence-Based Health Guidelines

In an age marked by overwhelming information and a rapidly aging global population, the need for accessible, comprehensible health information has never been more urgent. Although evidence-based health guidelines play a crucial role in supporting informed medical decision-making, their dense medical language and structural complexity often render them inaccessible to lay audiences. This study investigates the transformative role of Artificial Intelligence (AI) in enabling medical libraries to serve as dynamic platforms for promoting the accessible reading of such guidelines, thereby advancing public health literacy and equity.

A dual challenge emerges: on one hand, the expanding volume and sophistication of clinical guidelines; on the other, the unmet needs of vulnerable populations—such as the visually and hearing impaired, those with cognitive disabilities, low literacy skills, and the elderly—who often face significant barriers to comprehension. Conventional dissemination strategies fall short in bridging these gaps. While numerous countries have made progress in producing high-quality evidence-based guidelines, effective and inclusive public dissemination, particularly for non-medical audiences, remains insufficient. With their deep expertise in information access, educational outreach, and user-centered services, medical libraries are uniquely positioned to address this shortfall. AI technologies now offer a powerful means to extend their reach and impact.

This paper synthesizes current international and domestic developments in the promotion of accessible health guidelines. Globally, AI has demonstrated its potential through tools such as computer vision for environmental navigation and real-time speech recognition for communication. Specific to health, initiatives like the WHO’s multilingual digital health assistant and large language models have shown promise in simplifying complex medical texts. In China, policy frameworks supporting accessibility and AI-enabled assistive tools have evolved rapidly; however, a significant gap persists in the intelligent transformation of clinical guidelines into accessible, user-friendly formats.

To bridge this gap, we propose a comprehensive framework for AI-integrated services within medical libraries aimed at creating a multi-modal, inclusive reading experience for health guidelines. The framework encompasses four key strategies. First, AI-driven content simplification and summarization will employ natural language processing and large language models to produce plain-language explanations, concise digests, and multimedia outputs including audio, visual, and sign-language formats. Second, multi-modal presentation tools—such as text-to-speech engines, speech recognition systems, and image-to-text converters—will enable flexible, sensory-adaptive access to information. Third, intelligent recommendation engines and conversational agents will utilize user profiling to deliver personalized content and responsive health information support. Finally, the model underscores the indispensable role of human-AI collaboration: medical librarians and healthcare professionals must actively curate, verify, and refine AI-generated content to ensure scientific integrity and practical usability, supported by iterative feedback loops.

By transforming complex, text-heavy medical information into accessible, engaging formats, AI-augmented medical libraries can substantially elevate public health literacy. This model supports self-directed, informed health choices and helps close persistent information gaps among underserved populations. More broadly, it offers a replicable, forward-looking strategy that aligns with global health equity goals and national initiatives such as the "Healthy China 2030" plan. The findings lay critical groundwork for integrating emerging AI capabilities into the next generation of inclusive health information services.