PDF(Pubmed)
Abstract：
Artificial intelligence (AI) and language models such as ChatGPT-4 (Generative Pretrained Transformer) have made tremendous advances recently and are rapidly transforming the landscape of medicine. Cardiology is among many of the specialties that utilize AI with the intention of improving patient care. Generative AI, with the use of its advanced machine learning algorithms, has the potential to diagnose heart disease and recommend management options suitable for the patient. This may lead to improved patient outcomes not only by recommending the best treatment plan but also by increasing physician efficiency. Language models could assist physicians with administrative tasks, allowing them to spend more time on patient care. However, there are several concerns with the use of AI and language models in the field of medicine. These technologies may not be the most up-to-date with the latest research and could provide outdated information, which may lead to an adverse event. Secondly, AI tools can be expensive, leading to increased healthcare costs and reduced accessibility to the general population. There is also concern about the loss of the human touch and empathy as AI becomes more mainstream. Healthcare professionals would need to be adequately trained to utilize these tools. While AI and language models have many beneficial traits, all healthcare providers need to be involved and aware of generative AI so as to assure its optimal use and mitigate any potential risks and challenges associated with its implementation. In this review, we discuss the various uses of language models in the field of cardiology.
摘要：
人工智能（AI）和语言模型，如ChatGPT-4（生成预训练变压器）最近取得了巨大的进步，并正在迅速改变医学的格局。心脏病学是许多利用AI旨在改善患者护理的专业之一。生成AI,使用先进的机器学习算法，有可能诊断心脏病，并推荐适合患者的管理方案。这可以不仅通过推荐最佳治疗计划而且通过提高医师效率来导致改善的患者结果。语言模型可以帮助医生完成管理任务，让他们花更多的时间在病人护理上。然而,在医学领域使用人工智能和语言模型有几个问题。这些技术可能不是最新研究的最新技术，可能会提供过时的信息，这可能导致不良事件。其次,人工智能工具可能很昂贵，导致医疗费用增加，普通人群的可及性降低。随着AI变得越来越主流，人们也担心失去人情味和同理心。医疗保健专业人员需要接受充分的培训才能使用这些工具。虽然人工智能和语言模型有许多有益的特征，所有医疗保健提供者都需要参与并意识到生成AI，以确保其最佳使用并减轻与实施相关的任何潜在风险和挑战。在这次审查中,我们讨论了语言模型在心脏病学领域的各种用途。
