The hope and the hype of artificial intelligence for syncope management.

IF 4.4 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
European heart journal. Digital health Pub Date : 2025-06-26 eCollection Date: 2025-09-01 DOI:10.1093/ehjdh/ztaf061
Samuel L Johnston, E John Barsotti, Constantinos Bakogiannis, Artur Fedorowski, Fabrizio Ricci, Eric G Heller, Robert S Sheldon, Richard Sutton, Win-Kuang Shen, Venkatesh Thiruganasambandamoorthy, Mehul Adhaduk, William H Parker, Arwa Aburizik, Corey R Haselton, Alex J Cuskey, Sangil Lee, Madeleine Johansson, Donald Macfarlane, Paari Dominic, Haruhiko Abe, B Hygriv Rao, Avinash Mudireddy, Milan Sonka, Roopinder K Sandhu, Rose Anne Kenny, Giselle M Statz, Rakesh Gopinathannair, David Benditt, Franca Dipaola, Mauro Gatti, Roberto Menè, Alessandro Giaj Levra, Dana Shiffer, Giorgio Costantino, Raffaello Furlan, Martin H Ruwald, Vassilios Vassilikos, Milena A Gebska, Brian Olshansky
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引用次数: 0

Abstract

Aims: Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope.

Methods and results: We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable.

Conclusion: Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning-based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.

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人工智能对晕厥管理的希望和炒作。
目的:尽管在检测和治疗方面取得了进展,晕厥仍然是一种诊断挑战。心源性晕厥是死亡率的独立预测因子,很难与其他原因引起的短暂性意识丧失(TLOC)区分开来。本文探讨人工智能(AI)能否改善晕厥患者的评估和管理。方法与结果:我们进行文献回顾,并结合晕厥和人工智能领域专家的意见。TLOC的病因往往不清楚,住院标准含糊不清,诊断测试往往不能提供信息,而且评估费用高昂。留给患者的是没有答案的问题和有限的指导。人工智能(AI)有潜力通过处理大数据集、检测难以察觉的模式和协助临床医生来优化晕厥评估。然而,人工智能也有局限性,包括错误、缺乏人类同理心和不确定的临床用途。责任问题使其整合进一步复杂化。我们提出了三个观点:(i)人工智能对推进晕厥治疗至关重要;(ii)人工智能可以增强患者体验;(三)人工智能在晕厥护理中不可避免。结论:人工智能可以改善晕厥的诊断和管理,特别是通过基于机器学习的测试解释和可穿戴设备数据。然而,在复杂的决策中,它还没有超越人类的临床判断。当前的挑战包括对晕厥机制的理解、人工智能的可解释性、普遍性和临床整合。标准化的诊断方法、真实世界的验证和精心整理的数据集对取得进展至关重要。人工智能可能会提高效率和沟通,但也会引发对保密性、偏见、不公平和法律影响的担忧。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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