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腰椎间盘的深度学习诊断和治疗使用磁共振成像进行决策:一项回顾性研究

Yuanlong He¹, Zhong He², Yong Qiu³

¹Department of Spine Surgery, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, Jiangsu, China; Division of Spine Surgery, Department of Orthopedic Surgery, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, China.

World neurosurgery

|January 29, 2025

概括

人工智能 (AI) 增强了使用MRI扫描的腰椎间盘 (LDH) 诊断. 人工智能辅助的方法实现了94.7%的准确性,提高了专家的诊断速度和有效性.

科学领域:

医学成像分析医学成像分析
人工智能在医学中的应用
深度学习应用程序

背景情况:

腰椎间盘 (LDH) 是背部和腿部疼痛的常见原因.
诊断包括临床评估,体检和成像,MRI作为关键的诊断工具.
目前用于LDHMRI分析的AI研究通常集中在检测的存在上.

研究的目的:

评估人工智能辅助的方法在MRI上检测腰椎间盘 (LDH) 的诊断准确性和效率.
为了比较纯人工智能,纯人类和人工智能辅助诊断方法的性能.
评估人工智能集成对诊断决策时间的影响.

主要方法:

对接受手术评估的患者的MRI图像进行回顾性分析.
训练深度学习卷积神经网络 (CNN) 在MRI中检测LDH.
对纯人工智能,纯人类和人工智能辅助组的诊断准确度和决策时间的比较研究.

主要成果:

人工智能辅助的诊断方法获得了最高的准确率94.7%.
人工智能辅助诊断超越了纯人工智能驱动和纯人类诊断方法.
整合人工智能减少了诊断决策时间,而不会对准确性产生负面影响.

结论:

通过MRI,CNN可以有效地支持专家进行LDH的初始诊断和治疗计划.
人工智能和人类专业知识的结合提高了临床环境中的诊断准确性和效率.
人工智能辅助诊断在改善LDH管理的临床实践方面具有显著价值.

关键词:

卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.诊断诊断诊断诊断诊断腰椎椎间盘的发生磁共振成像技术磁共振成像技术治疗方法治疗方法

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