The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our systematic literature review demonstrates that ML-powered tools can alleviate the burden on healthcare systems. These tools can analyze significant amounts of medical data and potentially improve predictive and preventive healthcare.
The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from
... Show MoreCOVID-19 is a coronavirus disease caused by the severe acute respiratory syndrome. According to the World Health Organization (WHO), coronavirus-2 (SARS-CoV-2) was responsible for 87,747,940 recorded infections and 1,891,352 confirmed deaths as of January 9, 2021. Antibodies that target the Sprotein are efficient in neutralizing the virus. Methodology: 180 samples were collected from clinical sources (Blood and Nasopharyngeal swabs) and from different ages and genders at diverse hospitals in Baghdad / IRAQ between November 5, 2021, to January 20, 2022. All samples were confirmed infected with COVID-19 disease by RT-PCR technique. Haematology analysis and blood group were done for all samples, and Enzyme-Linked Immunosorbent Assay used an Ig
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreBackground: Coronavirus pandemic (COVID-19) has enormously affected various healthcare services including the one of community pharmacy. The ramifications of these effects on Iraqi community pharmacies and the measures they have taken to tackle the spread of COVID-19 is yet to be explored. In this cross sectional survey, infection control measures by community pharmacies in Sulaimani city/Iraq has been investigated.
Methods: Community pharmacists were randomly allocated to participate in a cross-sectional survey via visiting their pharmacies and filling up the questionnaire form.
Results and discussion:
... Show MoreThe study aims to measure the level of academic stress in the e-learning environment in three areas, students and their dealing with classmates, dealing with the professor and technical skills, and the nature and content of the curriculum among graduate students in the College of Education at King Khalid University during COVID-19 pandemic. This study was descriptive in nature (survey, comparative). The sample consisted of (512) male and female graduate students in the master's and doctoral programs. The Academic Stress Scale in the E-learning Environment designed by Amer (2021) was used. The results indicated a high level of academic stress among graduate students in the e-learning environment. The study also found that there were stati
... Show MoreThis article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss
... Show MoreThe rising prevalence of obesity-related glomerulopathy (ORG) occurs in accordance with the rising prevalence of obesity worldwide. Clinically ORG is manifested by slowly progressing microalbuminuria that may develop to clinically evident proteinuria. Pathological characteristics of ORG include glomerular hypertrophy in the presence or absence of focal segmental glomerulosclerosis (FSGS). ORG can develop into clinically overt chronic renal insufficiency or even end-stage kidney disease. This article reviews the most important mechanisms for the development of ORG; that are abnormal renal hemodynamics, stimulation of renin-angiotensin-aldosterone system (RAAS), impairment of insulin sensetivity, ectopic lipid deposition, adipose tissue cy
... Show MoreNumerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences.
An anal fissure which does not heal with conservative measures as sits baths and laxatives is a chronic anal fissure. Physiologically, it is the high resting tone of the internal anal sphincter that chiefly interferes with the healing process of these fissures. Until now, the gold standard treatment modality is surgery, either digital anal dilatation or lateral sphincterotomy. However, concerns have been raised about the incidence of faecal incontinence after surgery. Therefore, pharmacological means to treat chronic anal fissures have been explored. A Medline and pub med database search from 1986-2012 was conducted to perform a literature search for articles relating to the non-surgical treatment of chronic anal fissure. Pharmacological
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