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人工智能在阿尔茨海默氏症中的应用:一本书法分析分析

Sijia Song¹, Tong Li¹, Wei Lin¹

¹School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Frontiers in neuroscience

|March 3, 2025

概括

人工智能 (AI) 在阿尔茨海默病 (AD) 研究中越来越多地用于预测和诊断. 图书统计分析揭示了关键趋势和热点,强调了深度学习和任务分析作为未来的前沿.

科学领域:

在阿尔茨海默病 (AD) 研究中对人工智能 (AI) 应用的图书统计分析.
人工智能,神经科学和医疗信息学的交叉点上的跨学科研究.

背景情况:

人工智能在预测,诊断和分析阿尔茨海默病 (AD) 的应用是一个快速发展的领域.
本研究分析了2004-2023年的文献,以了解AI在AD研究中的作用.

研究的目的:

在过去二十年中,确定AI应用中的关键研究热点和趋势.
在AD研究中提供AI的文献统计概述.

主要方法:

在2004年至2023年间发表的2,316篇论文的图书统计分析,来源于科学网络核心集合.
使用Excel,Scimago Graphica,VOSviewer和CiteSpace进行视觉分析,绘制出版趋势,地理分布,机构贡献,关键期刊,有影响力的作者和新兴关键词的地图.
通过关键词和参考分析确定研究前沿.

主要成果:

自2018年以来出版物的显著增加表明该领域的快速增长.
美国,中国和英国是主要的贡献者. 伦敦大学和加利福尼亚大学系统是顶级机构.
关键的研究热点包括AD分期,早期诊断查,风险预测和疾病进展. "任务分析"从2021-2023年开始成为一个前沿话题.

结论:

在AD研究中的AI应用显示出实践进步的巨大潜力,深度学习 (DL) 是诊断的关键焦点.
未来的研究方向包括任务分析,多式联运数据集成和深度神经网络,用于识别风险因素和预测进展.
人工智能已经准备好将AD管理转变为更易于管理和潜在的可逆状态.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.在CiteSpace中使用CiteSpace.在VOSviewer中使用VOSviewer.人工智能是一种人工智能.文献计量分析的分析机器学习是机器学习.

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