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人工智能应用于的成像:当前状态和未来的前景

M Berger¹, R Licandro², K-H Nenning³

¹Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.

Revue neurologique

|April 2, 2025

概括

人工智能 (AI),包括深度学习 (DL) 和机器学习 (ML),正在彻底改变研究和神经影像. 这些人工智能工具旨在改善的诊断,治疗和预测结果.

科学领域:

神经学神经学
医疗成像医学成像
人工智能的人工智能

背景情况:

人工智能 (AI) 在医学研究中变得越来越重要,对瘤学有重大影响.
深度学习 (DL) 和机器学习 (ML) 是人工智能的核心组成部分,推动了研究的进步.

研究的目的:

探索AI在症神经成像中的应用.
研究AI在病变检测,发作焦点定位和预测术后结果方面的作用.
评估AI在区分患者与健康对照者的潜力.

主要方法:

在多种神经成像模式中研究各种AI驱动的方法.
专注于DL和ML技术来分析与有关的数据.

主要成果:

人工智能应用在病变检测,横向化和发性区域的局部化方面表现有前途.
人工智能工具正在开发中,用于预测术后结果,并将患者与健康个体区分开来.
计算能力的进步正在加速人工智能开发和治疗中的临床整合.

结论:

人工智能为症神经成像提供了一个变革性的机会,增强了诊断和治疗.
在临床实践中更广泛地采用人工智能,需要对患者数据安全采取强有力的监管措施.
未来的进展取决于促进合作和扩大开放访问数据集,以有效地训练ML和DL模型.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.的成像成像研究机器学习是机器学习.扣押检测的检测扣押检测

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