This study investigates the integration and impact of Large Language Models (LLMs), like ChatGPT, in India's healthcare sector. Our research employs a dual approach, engaging both general users and medical professionals through surveys and interviews respectively. Our findings reveal that healthcare professionals value ChatGPT in medical education and preliminary clinical settings, but exercise caution due to concerns about reliability, privacy, and the need for cross-verification with medical references. General users show a preference for AI interactions in healthcare, but concerns regarding accuracy and trust persist. The study underscores the need for these technologies to complement, not replace, human medical expertise, highlighting the importance of developing LLMs in collaboration with healthcare providers. This paper enhances the understanding of LLMs in healthcare, detailing current usage, user trust, and improvement areas. Our insights inform future research and development, underscoring the need for ethically compliant, user-focused LLM advancements that address healthcare-specific challenges.

翻译：本研究探究了大语言模型（如ChatGPT）在印度医疗保健领域的整合与影响。我们采用双重研究方法，分别通过问卷调查和访谈方式接触普通用户与医疗专业人员。研究结果显示，医疗专业人士重视ChatGPT在医学教育和初步临床场景中的应用价值，但因顾虑可靠性、隐私问题以及需与医学文献交叉验证而持谨慎态度。普通用户倾向于在医疗保健中采用AI互动，但对准确性和信任度仍存担忧。研究强调此类技术应辅助而非替代人类医疗专业知识，凸显了与医疗服务提供者协作开发大语言模型的重要性。本文深化了对医疗保健领域大语言模型的理解，详细阐述了当前应用现状、用户信任度及改进方向。我们的见解可为未来研究与发展提供参考，强调需推进符合伦理规范、以用户为中心且能应对医疗特有挑战的大语言模型创新。