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A Framework on a Computer Assisted and Systematic Methodology for Detection of Chronic Lower Back Pain Using Artificial Intelligence and Computer Graphics Technologies

机译:利用人工智能和计算机图形学技术检测慢性下腰痛的计算机辅助系统方法论框架

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Back pain is one of the major musculoskeletal pain problems that can affect many people and is considered as one of the main causes of disability all over the world. Lower back pain, which is the most common type of back pain, is estimated to affect at least 60 % to 80 % of the adult population in the United Kingdom at some time in their lives. Some of those patients develop a more serious condition namely Chronic Lower Back Pain in which physicians must carry out a more involved diagnostic procedure to determine its cause. In most cases, this procedure involves a long and laborious task by the physicians to visually identify abnormalities from the patient's Magnetic Resonance Images. Limited technological advances have been made in the past decades to support this process. This paper presents a comprehensive literature review on these technological advances and presents a framework of a methodology for diagnosing and predicting Chronic Lower Back Pain. This framework will combine current state-of-the-art computing technologies including those in the area of artificial intelligence, physics modelling, and computer graphics, and is argued to be able to improve the diagnosis process.
机译:背痛是可能影响许多人的主要肌肉骨骼疼痛问题之一,被认为是全世界致残的主要原因之一。下背痛是最常见的背痛类型,据估计在生活中的某个时候会影响英国至少60%至80%的成年人口。这些患者中有一些会出现更严重的病状,即慢性下腰痛,医生必须在其中进行更复杂的诊断程序以确定其原因。在大多数情况下,此过程需要医生进行繁重且费力的任务,才能从患者的磁共振图像中目视识别异常。在过去的几十年中,为支持该过程而取得的技术进展有限。本文对这些技术进步进行了全面的文献综述,并提出了一种诊断和预测慢性下腰痛的方法框架。该框架将结合当前最先进的计算技术,包括人工智能,物理建模和计算机图形学领域的技术,并被认为能够改善诊断过程。

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