Temsah Mohamad-Hani, Jamal Amr, Alhasan Khalid, Temsah Abdulkarim A, Malki Khalid H
Pediatric Intensive Care Unit, Pediatric Department, College of Medicine, King Saud University Medical City, King Saud University, Riyadh, SAU.
Family and Community Medicine Department, King Saud University, Riyadh, SAU.
Cureus. 2024 Oct 1;16(10):e70640. doi: 10.7759/cureus.70640. eCollection 2024 Oct.
This editorial explores the recent advancements in generative artificial intelligence with the newly-released OpenAI o1-Preview, comparing its capabilities to the traditional ChatGPT (GPT-4) model, particularly in the context of healthcare. While ChatGPT has shown many applications for general medical advice and patient interactions, OpenAI o1-Preview introduces new features with advanced reasoning skills using a processes that could enable users to tackle more complex medical queries such as genetic disease discovery, multi-system or complex disease care, and medical research support. The article explores some of the new model's potential and other aspects that may affect its usage, like slower response times due to its extensive reasoning approach yet highlights its potential for reducing hallucinations and offering more accurate outputs for complex medical problems. Ethical challenges, data diversity, access equity, and transparency are also discussed, identifying key areas for future research, including optimizing the use of both models in tandem for healthcare applications. The editorial concludes by advocating for collaborative exploration of all large language models (LLMs), including the novel , to fully utilize their transformative potential in medicine and healthcare delivery. This model, with its advanced reasoning capabilities, presents an opportunity to empower healthcare professionals, policymakers, and computer scientists to work together in transforming patient care, accelerating medical research, and enhancing healthcare outcomes. By optimizing the use of several LLM models in tandem, healthcare systems may enhance efficiency and precision, as well as mitigate previous LLM challenges, such as ethical concerns, access disparities, and technical limitations, steering to a new era of artificial intelligence (AI)-driven healthcare.
这篇社论探讨了随着新发布的OpenAI o1-Preview,生成式人工智能的最新进展,将其能力与传统的ChatGPT(GPT-4)模型进行比较,特别是在医疗保健领域。虽然ChatGPT已在一般医疗建议和患者互动方面展现出许多应用,但OpenAI o1-Preview引入了具有先进推理技能的新功能,采用了一种流程,使用户能够处理更复杂的医疗问题,如遗传疾病发现、多系统或复杂疾病护理以及医学研究支持。文章探讨了新模型的一些潜力以及可能影响其使用的其他方面,比如由于其广泛的推理方法导致响应时间较慢,但同时强调了其减少幻觉并为复杂医疗问题提供更准确输出的潜力。还讨论了伦理挑战、数据多样性、获取公平性和透明度,确定了未来研究的关键领域,包括在医疗保健应用中串联优化使用这两种模型。社论最后主张对所有大语言模型(LLMs),包括新出现的模型进行协作探索,以充分利用它们在医学和医疗保健提供方面的变革潜力。这种具有先进推理能力的模型为医疗保健专业人员、政策制定者和计算机科学家共同努力变革患者护理、加速医学研究和改善医疗保健结果提供了一个机会。通过串联优化使用多个大语言模型,医疗保健系统可以提高效率和精度,同时减轻以前大语言模型面临的挑战,如伦理问题、获取差距和技术限制,引领人工智能(AI)驱动的医疗保健新时代。