腰椎间盘突出症机器学习的研究进展△

Research progress on machine learning in the field of lumbar disc herniation

摘要:

腰椎间盘突出 （lumbar disc herniation, LDH） 是一种高发病率疾病，也是导致成年人下肢感觉运动障碍的常见原因。目前对于 LDH 的研究大多是传统的研究，但随着人工智能时代的到来，机器学习（machine learning, ML）逐渐登上了历史舞台。ML 可以利用计算机从大数据中“学习”复杂关系，并产生将大量协变量与感兴趣的目标变量联系起来的模型。具体功能包括但不限于病变检测和分类、图像自动分割、数据分析、放射特征提取、优先报告和研究分类以及图像重建。ML 处理数据的能力已达到相当高的水平。本文就基于 ML 在 LDH 方面的研究予以综述。

Abstract:

Lumbar disc herniation (LDH) is a highly prevalent disease and a common cause of sensory-motor disorders of the lower ex- tremities in adults. Most of the current research on LDH is traditional, however, with the advance of artificial intelligence, machine learning (ML) is gradually taking the historical stage. The ML use computers to learn complex relationships from big data and generate models that link a large number of covariates to the target variable of interest, including but not limited to lesion detection and classification, automatic image segmentation, data analysis, radiological feature extraction, priority reporting and study classification, and image reconstruction. The ML has reached a considerable level of ability to process data. This paper reviews current ML researches in LDH.