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罕见疾病中的人工智能:对临床影响的研究

Ana M B Amorim¹, Urszula Orzeł², Ana B Caniceiro¹

¹CNC - Center for Neuroscience and Cell Biology, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra 3004-504, Portugal; PhD in Biosciences, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, Coimbra 3000-456, Portugal; Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, Coimbra 3000-456, Portugal; PURR.AI, Rua Pedro Nunes, IPN Incubadora, Ed C, Coimbra 3030-199, Portugal; CoLAB4Ageing - Sítio Paço das Escolas, Reitoria da Universidade de Coimbra, Coimbra 3000-530, Portugal.

Trends in pharmacological sciences

|November 26, 2025

概括

人工智能 (AI) 可以通过整合各种数据来加速罕见疾病 (RD) 诊断和治疗发现. 对人工智能来说,解决技术,伦理和基础设施方面的挑战至关重要.

科学领域:

医疗信息学医疗信息学
基因组学就是基因组学.
人工智能的人工智能

背景情况:

罕见疾病 (RDs) 影响全球超过4亿人,许多人面临诊断延迟和有限的治疗选择.
现有的人工智能 (AI) 工具用于 RD 往往仍处于概念验证阶段,阻碍了临床翻译.
关键的挑战包括数据稀缺,隐私问题和算法偏见,限制AI对患者护理的影响.

研究的目的:

审查人工智能的最新进展,包括生成模型,联合学习 (FL) 和可解释人工智能 (XAI),以应对研发和开发方面的挑战.
确定关键的技术,伦理和基础设施优先事项,以将人工智能创新转化为罕见疾病患者的临床益处.
强调公平,公平数据原则和全球协调在开发和部署人工智能的发展和部署的重要性.

主要方法:

对罕见病人工智能近期发展的文献综述.
分析新兴的人工智能技术,如生成模型,联合学习和可解释的人工智能.
对临床翻译的技术,伦理和基础设施要求的综合.

主要成果:

生成模型,FL和XAI的进步开始克服数据稀缺性,隐私和对R&D的AI的偏见问题.
该审查概述了包括公平,公平数据原则和全球合作在内的具体优先事项.
这些优先事项对于弥合人工智能创新与实实在在的患者利益之间的差距至关重要.

结论:

人工智能对加速罕见疾病诊断和治疗发现具有重大前景.
将人工智能的潜力转化为临床现实需要对伦理考虑,数据可访问性 (FAIR原则) 和国际合作进行协调关注.
技术,伦理和基础设施因素的战略优先考虑对于实现人工智能在罕见疾病管理中的全部临床影响至关重要.

关键词:

人工智能的人工智能是人工智能.早期诊断早期诊断早期诊断卫生公平性健康公平性多式联运数据是多式联运数据.个性化治疗个性化治疗罕见的疾病罕见的疾病

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