Genetic Testing of Huntington’s Disease by Facial Examination of a Mankind using AI Programs

S. Feroze, S. Nasim
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Abstract

This Genetic disorder is considered as one of the major challenges faced by Medical Sciences as it is inherited by humans from one generation to another. With an increasing number of natives of the World at a higher rate, it causes a major impact on information society socially and economically during their lifetime. The citizens of Pakistan and Indian sub continents are facing genomic disease in probably high frequency as compared to other continents. Occurrence of congenital diseases in Pakistan results in higher percentages of unusual genetic diseases especially in children. After analyzing all the current scenarios, some goals and objectives were settled in order to facilitate and give general awareness to people. The objectives of systematic review are evaluation of diagnostic accuracy of AI for the identification of genome contributions to the pathogenesis of Huntington’s disease through facial probe AI to accurately identify genetic disorders. The narrative review is performed in Ned University. In this proceeding sequence, 30 cases of both Normal and Genetically affected Patients were documented in which some certain sorts of tests were performed by using facial recognition. For this FR test, at first a combo list of information of all six emotions of a human being i.e. (Happy, Sorrow, Amazed, Fear, Anger, Revulsion) is gathered in the form of mutated images, which was then later be arranged into a pseudo-random order. Now with the help of Vision Technology we have applied some CV Techniques for the extraction of large pattern sets of features. Lastly the purpose of ML and DL techniques is to receive and compare those morphed image data from the Facial Database in order to identify each of six different emotions of HD & Normal Person. This whole procedure is conducted in real time. Hence in this way we may recognize the HD genetic disorder among the people in an efficient way. The detailed procedure is explained in the Methodology section of this narrative review. Implementation of this process will bring an amazing accountability in suppressing Genetic testing HD in clinical practice.
利用人工智能程序对人类进行面部检查,从而进行亨廷顿氏病的基因检测
这种遗传疾病被认为是医学科学面临的主要挑战之一,因为它是人类一代一代遗传给另一代的。随着世界上土著人口的不断增加,在他们的一生中,它对信息社会的社会和经济产生了重大影响。与其他大陆相比,巴基斯坦和印度次大陆的公民面临基因组疾病的频率可能很高。在巴基斯坦,先天性疾病的发生导致罕见遗传疾病的比例较高,特别是在儿童中。在分析了所有当前的场景后,确定了一些目标和目的,以方便并使人们普遍认识到。本系统综述的目的是评估人工智能在识别亨廷顿病发病机制中基因组贡献的诊断准确性,通过面部探针人工智能准确识别遗传疾病。叙事回顾在内德大学进行。在此程序序列中,记录了30例正常和遗传影响患者,其中使用面部识别进行了某些类型的测试。对于这个FR测试,首先以突变图像的形式收集人类所有六种情绪(快乐,悲伤,惊讶,恐惧,愤怒,厌恶)的信息组合列表,然后将其排列成伪随机顺序。现在,在视觉技术的帮助下,我们已经应用了一些CV技术来提取大型模式集的特征。最后,ML和DL技术的目的是接收和比较来自面部数据库的变形图像数据,以识别高清和正常人的六种不同情绪。整个过程是实时进行的。因此,通过这种方式,我们可以有效地识别人群中的HD遗传疾病。详细的程序在这篇叙述性评论的方法论部分解释。这一过程的实施将在临床实践中抑制HD基因检测方面带来惊人的责任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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