Navigating the uncommon: challenges in applying evidence-based medicine to rare diseases and the prospects of artificial intelligence solutions.

IF 2.3 2区 哲学 Q1 ETHICS Medicine Health Care and Philosophy Pub Date : 2024-09-01 Epub Date: 2024-05-09 DOI:10.1007/s11019-024-10206-x
Olivia Rennie
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Abstract

The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow movement towards improved understanding of pathophysiology and treatments compared with more common illnesses. The push towards evidence-based medicine (EBM), which prioritizes certain types of evidence over others, poses a particular issue when mapped onto rare diseases, which may not be feasibly investigated using the methodologies endorsed by EBM, due to a number of constraints. While other trial designs have been suggested to overcome these limitations (with varying success), perhaps the most recent and enthusiastically adopted is the application of artificial intelligence to rare disease data. This paper critically examines the pitfalls of EBM (and its trial design offshoots) as it pertains to rare diseases, exploring the current landscape of AI as a potential solution to these challenges. This discussion is also taken a step further, providing philosophical commentary on the weaknesses and dangers of AI algorithms applied to rare disease research. While not proposing a singular solution, this article does provide a thoughtful reminder that no 'one-size-fits-all' approach exists in the complex world of rare diseases. We must balance cautious optimism with critical evaluation of new research paradigms and technology, while at the same time not neglecting the ever-important aspect of patient values and preferences, which may be challenging to incorporate into computer-driven models.

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驾驭罕见病:将循证医学应用于罕见病的挑战和人工智能解决方案的前景。
长期以来,罕见病研究一直是医学研究人员面临挑战的一个领域,与更常见的疾病相比,罕见病在提高对病理生理学和治疗方法的认识方面进展缓慢,令人痛苦。循证医学(EBM)将某些类型的证据置于其他证据之上,这对罕见病的研究提出了一个特殊的问题,由于一些限制因素,使用 EBM 认可的方法对罕见病进行研究可能并不可行。虽然有人提出了其他试验设计来克服这些局限性(成功率不一),但最近被热烈采用的可能是将人工智能应用于罕见病数据。本文批判性地研究了 EBM(及其试验设计分支)在罕见病方面的缺陷,探讨了人工智能作为解决这些挑战的潜在方案的现状。此外,本文还进一步对应用于罕见病研究的人工智能算法的弱点和危险进行了哲学评述。这篇文章虽然没有提出单一的解决方案,但却深思熟虑地提醒我们,在复杂的罕见病世界中不存在 "放之四海而皆准 "的方法。我们必须在谨慎乐观与对新研究范例和技术的批判性评估之间保持平衡,同时也不能忽视患者价值观和偏好这个永远重要的方面,将其纳入计算机驱动的模型可能具有挑战性。
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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来源期刊
CiteScore
4.30
自引率
4.80%
发文量
64
期刊介绍: Medicine, Health Care and Philosophy: A European Journal is the official journal of the European Society for Philosophy of Medicine and Health Care. It provides a forum for international exchange of research data, theories, reports and opinions in bioethics and philosophy of medicine. The journal promotes interdisciplinary studies, and stimulates philosophical analysis centered on a common object of reflection: health care, the human effort to deal with disease, illness, death as well as health, well-being and life. Particular attention is paid to developing contributions from all European countries, and to making accessible scientific work and reports on the practice of health care ethics, from all nations, cultures and language areas in Europe.
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