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对于慢性脏病的人工智能辅助医学图像分析的当前进展:文献综述
Dan Zhao1, Wei Wang2, Tian Tang1
1Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China.
Computational and structural biotechnology journal
|June 19, 2023
概括
人工智能 (AI) 增强了慢性病 (CKD) 诊断的医学成像. 人工智能工具分析微妙的成像特征,帮助早期检测,评估和预测CKD.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 慢性病 (CKD) 是一个全球性健康问题,患病率不断增加.
- 高血压和糖尿病是导致CKD的主要危险因素.
- 医学成像对于非侵入性检测CKD中脏结构异常至关重要.
研究的目的:
- 在CKD诊断和管理中提供AI辅助医学图像分析的概述.
- 突出AI在识别CKD微妙成像特征方面的作用.
- 探索人工智能的潜力,以改善早期检测和预后评估CKD.
主要方法:
- 审查最近关于人工智能应用在医疗图像分析中对CKD的研究.
- 专注于基于放射学和深度学习的AI算法.
- 分析AI在识别宏观和微观脏异常方面的实用性.
主要成果:
- 人工智能辅助医学成像显示出作为CKD临床支持工具的有效性.
- 人工智能算法改善了早期检测,病理评估和预后评估.
- 人工智能有助于识别和管理各种CKD形式,包括自体主导多囊性病.
结论:
- 人工智能辅助的医学图像分析为诊断和管理CKD提供了重大潜力.
- 人工智能可以增强临床医生通过成像检测和评估CKD的能力.
- 在医学成像中进一步整合人工智能对推进CKD护理充满希望.
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