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![Figure 4: A woman wearing a flu mask during a pandemic [51]](profile/Abdel-Hameed-Al-Mistarehi/publication/360458415/figure/fig4/AS:1153567268319235@1652043277861/A-woman-wearing-a-flu-mask-during-a-pandemic-51_Q320.jpg)
![Figure 5: New York City in 1918 [52]](profile/Abdel-Hameed-Al-Mistarehi/publication/360458415/figure/fig5/AS:1153567268323335@1652043277881/New-York-City-in-1918-52_Q320.jpg)
The epidemic is an imminent danger that all humans fear, as it does not differentiate between anyone, whether small or old, rich or poor. It is characterized by its ability and super speed to conquer the world and its primary goal is to target humans and eradicate their lives. In this article, the authors decided to provide a brief historical overv...
Citations
... In addition, the data brought from all contact points with clients and customers can be used, where if it is managed in a very acceptable manner, it will support organisations in creating customised marketing responses, making very cool and new ideas, and designing professional products and services. In other words, it will provide high value to customers and gain a competitive advantage that puts the organisation in the forefront [30][31][32][33][34][35][36][37][38][39]. ...
Deep learning has become a favoured trend in many applications serving humanity in the past few years. Since deep learning seeks useful investigation and can learn and train huge amounts of unlabelled data, deep learning has been applied in many fields including the medical field. In this article, the most noteworthy applications of deep learning are presented shortly and positively, they are image recognition, automatic speech recognition, natural language processing, drug discovery and toxicology, customer relationship management, recommendation systems and bioinformatics. The report concluded that these applications have a significant and vital role in all areas of life.
... As a result, it was able to reach somewhat sufficient stages. For example, what occurred at the end of 20219 with the spread of the COVID-19 pandemic and the death of many people, artificial intelligence was able to control the spread of the virus, track cases of infection and analyse patient data with high speed and accuracy [51][52][53][54][55]. So, without artificial intelligence, the health sector is not working properly. ...
Nowadays, artificial intelligence, machine learning, and deep learning are among the most popular and applied topics in many scientific and life fields that serve humanity. This science seeks to impose itself strongly on the various activities and academic circles and information science. Artificial intelligence techniques have proven their worth to be important in many fields, especially in the medical fields, business administration, military applications, communications, and many others. In short, artificial intelligence is from another world that will be of great importance in the future. In this article, the importance of digitisation and artificial intelligence in the healthcare sector will be addressed, what services they provide to this sector, and how they contribute to the service of healthcare workers and patient satisfaction. This article concluded that artificial intelligence and digital technologies are of great importance in the healthcare sector and can never be dispensed with.
... Fashion images are among the most difficult images because fashions are a pack of colours, additions, different characteristics and depth of classification. In addition, deep learning techniques have been employed to analyse images of COVID-19 patients to a large extent, as these techniques have contributed to diagnosing the condition of patients and determining the infection rate with the virus [43][44][45][46][47][48]. In recent years, many algorithms have been designed that contribute to analysing a wide range of complex medical images with satisfactory time periods [49][50][51][52]. ...
Deep learning techniques have become vital in many fields in the modern era because they are excellent at analysing and predicting real big data to act in different situations. Although it is marvellous in many aspects, it is prone to misinterpretation of data, so teams of experienced specialists cannot be dispensed with in following up on the execution stages of data analysis. Convolutional Neural Network is one of the most significant deep learning techniques. It is widely employed in visual image analysis. In this article, R-CNN and Fast R-CNN are summarised and compared and are the best in image analysis. This article concluded that the most suitable performance is for Fast R-CNN in testing and training.
Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are complex images in their interpretation. In this article, two deep convolutional neural network (DCNN) classifiers, such as Inception-v2 and VGG-16, are utilized to detect COVID-19 from a set of chest X-ray images. The dataset for this article was collected from the Kaggle platform (COVID-19 Radiography Database) and consists of images of positive and healthy people. This article concludes that the most suitable performance is the Inception-v2 classifier, which has achieved an accuracy of 97% in comparison to the VGG-16 classifier, which has achieved an accuracy of 93%.
