COVID-19 Detection from CBC using Machine Learning Techniques

Abstract

Covid-19 pandemic has seriously affected the mankind with colossal loss of life around the world. There is a critical requirement for timely and reliable detection of Corona virus patients to give better and early treatment to prevent the spread of the infection. With that being said, current researches have revealed some critical benefits of utilizing complete blood count tests for early detection of COVID-19 positive individuals. In this research we employed different machine learning algorithms using full blood count for the prediction of COVID-19. These algorithms include: “K Nearest Neighbor, Radial Basis Function, Naive Bayes, kStar, PART, Random Forest, Decision Tree, OneR, Support Vector Machine and Multi-Layer Perceptron”. Further, “Accuracy, Recall, Precision, and F-Measure” are the performance evaluation measures that are utilized in this study.

An intelligent deep convolutional network based COVID-19 detection from chest X-rays

“…Consistent image exposure and luminance discrepancies within databases of each scanning mode were shown to be remarkably problematic, and numerous investigators have stated that medical records enhancement techniques are extremely vulnerable to changes in intensity values [25] . According to an investigation, an advanced analytical state's effectiveness demands that “the brightness of same material must always be equal in one photo and not fluctuate with the tissue's position.” When applied to the multiple photos used in classification techniques, this principle implies that all photographs in the sample sets of data ought to have identical intensity for the same tissue across the board as well as inside a single picture [26] .…”

The Transformational Leadership of the Founding Leaders of the United Arab Emirates: Sheikh Zayed Bin Sultan Al Nahyan and Sheikh Rashid Bin Saeed Al Maktoum

“…One leadership concept is the heroic or great man leadership, which appeared in a series of lectures by Thomas Carlyle in 1840 [77], in which he tried to remove the myths about the concept of the heroic leader who has supernatural qualities [78]. Other scholars, e.g., [79] found in an experiment three leadership styles that are autocratic [80][81], democratic, and laissez-faire, [82][83] found in a literature review several traits that could be standing behind the quality of leadership, e.g., risk taking, self-confidence, drive for responsibility and task completion [84], persistence in pursuit of goals, Weber listed in his book "Economy and Society" published in German for the first time three types of authority, i.e., 1) rational or legal authority or transactional leadership, which enable those who are elevated to authority to issue commands, 2) [2][85] traditional authority, which rest on a belief in the sanctity of immemorial traditions and the legitimacy of those exercising authority under them, and 3) the charismatic authority, which rest on devotion to the exceptional sanctity, heroism or exemplary character of a person, and of the order revealed by him [86][87], and [68][10] proposed the contingency leadership model, which state that the leader is effective in some circumstances and ineffective in other circumstances based on the leader and member abilities [88], which are among the most significant predictors of group performance and reflects the level of leader influence over the task itself.…”

The Internet’s Role in Undermining the Credibility of the Healthcare Industry

“…The infodemic's impact on the credibility of the COVID-19 vaccination fundamentally changed the way the public viewed the vaccine as a legitimate preventative measure to COVID-19 infections. As trials of different versions of the vaccine began, popular social media platforms such as Facebook, Instagram, and Twitter began circulating posts with dramatized infographics, inflated statistics, and false information [49,50,51,52,53,54,55]. These posts perpetuated antivaccination sentiment from a large majority of the global population, resulting in panic and mistrust.…”