Detection of Novel Corona Virus Using Machine Learning and Image Recognition

Dhruv Garg and Saurabh Gautam
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Abstract

In the recent past whole of the world has come to a standstill due to a novel airborne virus. The airborne nature of this disease has made it highly contagious which has led to a great number of people being infected very fast. This requires a new method of testing that is faster and more precise. Machine Learning has allowed us to develop sophisticated self-learning models that can learn from data being fed and decide on entirely new options. In the past we have used different Machine Learning algorithm to make models on different biomedical dataset to detect various kind of acute or chronic diseases. Here we have developed a model that successfully detects severe cases of Novel corona virus affected person with great precision.
利用机器学习和图像识别检测新型冠状病毒
最近,由于一种新型空气传播病毒,整个世界都陷入了停顿。这种疾病的空气传播特性使其具有高度传染性,导致许多人很快被感染。这就需要一种更快、更精确的新检测方法。机器学习使我们能够开发复杂的自我学习模型,这些模型可以从输入的数据中学习,并做出全新的选择。在过去,我们使用不同的机器学习算法在不同的生物医学数据集上建立模型来检测各种急慢性疾病。在这里,我们开发了一个模型,成功地检测出严重的新型冠状病毒感染者,精度很高。
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