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.
A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
... Show MoreBackground: coronavirus 19 is a beta-coronavirus, enveloped and roughly spherical with approximately 60 to 140 nm in diameter with positive-sense single-stranded RNA genome.
Objectives: Measurement of interleukin 6 (IL6) level in a group of patients with confirmed Covid19 infection and its correlation with many hematological and biochemical parameters , mainly lymphocyte , neutrophil count and their ratio , platelet count , serum ferritin , C reactive protein as well as D-dimer level
Subjects and Methods: This study was conducted on 60 PCR positive patients variably affected by COVID-19 , cases collected sequentially from June till November 20
... Show MoreAccurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty
... Show MoreThe map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
... Show MoreHuge efforts are being made to control the spread and impacts of the coronavirus pandemic using vaccines. However, willingness to be vaccinated depends on factors beyond the availability of vaccines. The aim of this study was three-folded: to assess children’s rates of COVID-19 Vaccination as reported by parents, to explore parents’ attitudes towards children’s COVID-19 vaccination, and to examine the factors associated with parents’ hesitancy towards children’s vaccination in several countries in the Eastern Mediterranean Region (EMR).
Abstract: Coronavirus disease 2019 (COVID-19) is an infectious disease with severe acute respiratory syndrome and first recognized in Wuhan, China, and it has since spread to the world, resulting in the coronavirus pandemic to 2020. The present study aimed to evaluate Molecular study of some types of vaginal fungi isolated from recovered women from Covid-19 in Baghdad governorate. The study was conducted on 213 samples collected between December 2021 and March 2022, where the number of positive samples reached 188 with percentage 88.26%, while the number of negative samples reached 25 with percentage 11.73% by taking vaginal swabs from various female patients in Al- Kadhimiya Teaching Hospital. Three of Candida spp. were isolated: Candida a
... Show MorePharmaceutical care is a patient-centered, outcomes oriented practice that requires the pharmacist to work in concert with the patient and the patient’s other healthcare providers to promote health, to prevent disease, and to assess, monitor, initiate, and modify medication use to assure that drug therapy regimens are safe and effective. In addition, the presence of clinical pharmacists has led to a higher quality of patient education and provision of complete detailed information for patients. In developed countries Pharm D has become the professional degree for practice of Pharmacy. The graduates will be enrolled in a pharmacy residency program; admission to the residency programs is available to Pharm D graduates of an accredit
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