Kumar Harekrishna
Department of Electronics and Communication, GLA University, Mathura, 281406 India.
Multimed Tools Appl. 2022;81(10):14217-14245. doi: 10.1007/s11042-022-12450-w. Epub 2022 Feb 25.
As everyone knows that in today's time Artificial Intelligence, Machine Learning and Deep Learning are being used extensively and generally researchers are thinking of using them everywhere. At the same time, we are also seeing that the second wave of corona has wreaked havoc in India. More than 4 lakh cases are coming in 24 h. In the meantime, news came that a new deadly fungus has come, which doctors have named Mucormycosis (Black fungus). This fungus also spread rapidly in many states, due to which states have declared this disease as an epidemic. It has become very important to find a cure for this life-threatening fungus by taking the help of our today's devices and technology such as artificial intelligence, data learning. It was found that the CT-Scan has much more adequate information and delivers greater evaluation validity than the chest X-Ray. After that the steps of Image processing such as pre-processing, segmentation, all these were surveyed in which it was found that accuracy score for the deep features retrieved from the ResNet50 model and SVM classifier using the Linear kernel function was 94.7%, which was the highest of all the findings. Also studied about Deep Belief Network (DBN) that how easy it can be to diagnose a life-threatening infection like fungus. Then a survey explained how computer vision helped in the corona era, in the same way it would help in epidemics like Mucormycosis.
众所周知，在当今时代，人工智能、机器学习和深度学习被广泛应用，研究人员普遍想在各个领域使用它们。与此同时，我们也看到新冠疫情的第二波在印度肆虐。24小时内新增病例超过40万例。在此期间，有消息称出现了一种新的致命真菌，医生将其命名为毛霉菌病（黑真菌）。这种真菌在许多邦也迅速传播，为此各邦已将这种疾病列为流行病。借助我们当今的设备和技术，如人工智能、数据学习，找到治疗这种危及生命的真菌的方法变得非常重要。研究发现，与胸部X光相比，CT扫描拥有更充分的信息，评估有效性更高。之后，对图像处理的步骤，如预处理、分割等进行了研究，发现使用线性核函数从ResNet50模型和支持向量机分类器中检索到的深度特征的准确率为94.7%，这是所有研究结果中最高的。还研究了深度信念网络（DBN），探讨诊断像真菌这样危及生命的感染有多容易。然后一项调查解释了计算机视觉在新冠疫情时代是如何发挥作用的，同样，它在毛霉菌病等流行病中也会有所帮助。
