人工智能支持的放射学-当前状态和批判性审查
Rafał Obuchowicz1, Julia Lasek2, Marek Wodziński3
1Department of Diagnostic Imaging, Jagiellonian University Medical College, 30-663 Krakow, Poland.
Diagnostics (Basel, Switzerland)
|February 13, 2025
概括
人工智能 (AI) 正在彻底改变诊断成像,特别是卷积神经网络 (CNN),提高准确性和效率. 这项研究审查了AI.
科学领域:
- 医学成像和人工智能 医学成像和人工智能
- 放射学和诊断技术的发展
- 医疗信息学和人工智能应用
背景情况:
- 人工智能 (AI) 正在改变依赖于人类认知的领域,神经网络正在推进数据处理.
- 卷积神经网络 (CNN) 和GPU技术显著提高了图像识别精度和计算效率.
- 人工智能在放射学中的应用为模式检测和分类提供了更高的诊断准确性和效率.
研究的目的:
- 审查基于AI的成像应用程序的进展,以提供诊断支持.
- 专注于CNN的作用,监管挑战和诊断成像中的劳动力影响.
- 分析AI产品开发趋势和医学成像中的关键应用领域.
主要方法:
- 从2017年到2020年对人工智能产品开发趋势的分析.
- 确定AI产品在医学成像 (神经成像,胸部成像,CT,MRI) 中的主要重点领域.
- 在高发病率疾病 (肺癌,中风,乳腺癌) 中对人工智能工具应用的审查.
- 对AI医疗器械的监管合规性 (MDD,MDR类IIa/I) 的检查.
主要成果:
- 神经成像,胸部成像,CT和MRI是人工智能产品的主要领域.
- 人工智能工具的目标是肺癌,中风和乳腺癌等高患病率的疾病.
- 人工智能产品开发从2017-2020年激增,在2020年达到顶峰,随后稳定.
- 大多数AI产品符合MDD和MDR下的中等风险标准.
结论:
- 人工智能,特别是CNN,在提高诊断成像和支持方面具有变革性的潜力.
- 监管合规对于放射学AI产品开发至关重要.
- 人工智能在诊断成像中的整合为人类劳动带来了机遇和潜在的挑战.
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