基于视频数据的人工智能分析对面瘫进行客观分级

Stewart McGrenary, B. O'Reilly, J. Soraghan
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引用次数: 25

摘要

面瘫是一种使人衰弱的疾病,患者会经历左侧或右侧面神经的单侧瘫痪。对病人的病情进行基于证据的评估几乎是不可能的,因为目前所有的评分标准都是主观的。一个定量的、实用的、可靠的系统将是神经根学领域的宝贵工具。这里展示的是一个系统,它可以智能地量化来自14个受试者的43个测试视频中的面部损伤。使用人工神经网络,系统的平均均方误差为1.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Objective grading of facial paralysis using artificial intelligence analysis of video data
Facial paralysis is a debilitating condition in which sufferers experience unilateral paralysis of the left or right facial nerve. An evidence based assessment of a patient's condition is almost impossible because all current grading scales are subjective. A quantitative, practical, reliable system would be an invaluable tool in this field of neurootology. Demonstrated here is a system which intelligently quantifies the facial damage in 43 testing videos from 14 subjects. Using an artificial neural network the average mean squared error for the system is 1.6%.
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