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Quantum Deep Learning For Phoniatrics Biomarker Based Disease Detection Deep Learning Model For Disease Detection By Phoniatrics Biomarkers Using Quantum Computation

机译:量子深度学习用于基于氧化生物标志物的疾病检测深度学习模型用于基于氧化生物标志物的疾病检测,采用量子计算

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It is known that humans phoniatrics changes while suffering from diseases and phoniatrics based analysis is on the rise with more data flowing in and used in artificial intelligence. Phoniatrics biomarkers are being discovered and implemented for the detection of diseases with the help of machine learning which is still a huge challenge. This is a tough challenge due to the computation power required and the implementation of neural nets. While there are some conventional neural nets are being used for phoniatrics analysis, still it takes a lot of computation time. In the era of quantum computation, it will be easy to implement the deep Boltzmann machine neural net on a quantum computer model. This helps in providing a solution for detection of disease using the various phoniatrics biomarkers to access a quantum based deep learning model to provide insights for the detection of disease.
机译:众所周知,人类的声音变化在患病的同时,基于声音的分析也在不断增加,越来越多的数据流入并用于人工智能。在机器学习的帮助下,已发现并实施了用于检测疾病的Phonictrics生物标记物,这仍然是一个巨大的挑战。由于所需的计算能力和神经网络的实现,这是一个艰巨的挑战。尽管有一些常规的神经网络用于语音分析,但仍需要大量的计算时间。在量子计算时代,在量子计算机模型上实现深层Boltzmann机器神经网络将很容易。这有助于提供使用各种语音生物标记物访问基于量子的深度学习模型以提供疾病检测见解的疾病检测解决方案。

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