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从特定任务到医疗诊断的通用人工智能的道路:一个图书识别分析

Chuheng Chang¹, Wen Shi², Youyang Wang³

¹Department of General Practice (General Internal Medicine), Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Computers in biology and medicine

|March 11, 2024

概括

医疗诊断中的人工智能 (AI) 正在迅速发展,从特定任务发展到通用应用. 数据质量和算法等关键因素推动了进步,而可解释性和稳定性仍然是挑战.

科学领域:

医疗信息学医疗信息学
计算机科学计算机科学
人工智能的人工智能

背景情况:

人工智能 (AI) 在医疗诊断方面显示出巨大潜力.
人工智能利用各种数据 (成像,实验室测试,记录) 用于医疗应用.
了解AI在诊断方面的发展对于临床整合至关重要.

研究的目的:

在医学诊断中对AI进行文献计量分析.
探索从特定任务到通用AI的演变.
确定发展因素和合作趋势.

主要方法:

科学网络文章的图书统计分析 (2010-2023年).
使用VOSviewer,R包Bibliometrix和CiteSpace进行分析.
检查了协作网络和关键词.

主要成果:

医疗诊断人工智能的快速增长,专注于图像分析,疾病预测和决策支持.
观察到研究人员和机构之间的全球合作网络.
确定数据质量,算法设计和计算能力是关键的开发因素.

结论:

医疗诊断中的人工智能正在向通用,多式联运应用发展.
挑战包括模型的可解释性,稳定性和平等性.
跨学科的合作对于克服挑战和在诊断领域推进AI至关重要.

关键词:

人工智能的人工智能是人工智能.图书统计学分析诊断诊断诊断诊断医学医学医学医学医学网络可视化网络可视化

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