The Practices of Artificial Intelligence Techniques and Their Worth in the Confrontation of COVID-19 Pandemic: A Literature Review

Today, the medical society is living in the era of artificial intelligence, which is developed and becomes more famous thanks to the coronavirus disease of 2019 (COVID-19) pandemic, which has given the space for artificial intelligence to appear more influential in analyzing medical data and providing very accurate results. This science has deservedly been able to achieve an excellent and vital position among healthcare workers, and it has become a necessary element of their work because of its a great potential for practical decision-making. The prospects of using intelligent systems in the medical field are deemed essential in the health division due to their ability to analyze big data and give exact results, aiming to improve the health of citizens and save their lives. In this article, a set of important information about the vital role of artificial intelligence in the medical field is highlighted. In addition, how this science does manage to confront SARS‐CoV‐2 by highlighting a set of investigations and analyses in predicting the spread of the virus, tracking infections, and diagnosis of cases through chest x-ray images of COVID-19 patients. The database of this article covered more than 40 studies between 2020 and 2021 and investigated the effects of utilizing artificial intelligence techniques in analyzing SARS‐CoV‐2 data. These studies are gathered from PubMed, NCBI, google scholar, Medrxiv, and other sites. This article includes a plethora of information about artificial intelligence and SARS‐CoV‐2. The findings confirm that artificial intelligence has a significant role in the healthcare domain, and it is advised to utilize its applications in the decision-making method.

Effectiveness of interactive teaching intervention on medical students' knowledge and attitudes toward stem cells, their therapeutic uses, and potential research applications

Background: Stem cell science is rapidly developing with the potential to alleviate many non-treatable diseases. Medical students, as future physicians, should be equipped with the proper knowledge and attitude regarding this hopeful field. Interactive teaching, whereby the teachers actively involve the students in the learning process, is a promising approach to improve their interest, knowledge, and team spirit. This study aims to evaluate the effectiveness of an interactive teaching intervention on medical students' knowledge and attitudes about stem cell research and therapy. Methods: A pre-post test study design was employed. A six-session interactive teaching course was conducted for a duration of six weeks as an intervention. Pre- and post-intervention surveys were used. The differences in the mean scores of students' knowledge and attitudes were examined using paired t-test, while gender differences were examined using an independent t-test. Results: Out of 71 sixth-year medical students from different nationalities invited to participate in this study, the interactive teaching course was initiated by 58 students resulting in a participation rate of 81.7%. Out of 58 students, 48 (82.8%) completed the entire course. The mean age (standard deviation) of students was 24 (1.2) years, and 32 (66.7%) were males. The results showed poor knowledge about stem cells among the medical students in the pre-intervention phase. Total scores of stem cell-related knowledge and attitudes significantly improved post-intervention. Gender differences in knowledge and attitudes scores were not statistically significant post-intervention. Conclusions: Integrating stem cell science into medical curricula coupled with interactive learning approaches effectively increased students' knowledge about recent advances in stem cell research and therapy and improved attitudes toward stem cell research and applications. Keywords: Arab; Attitudes; Education; Interactive teaching; Jordan; Knowledge; Medical curriculum; Stem cells; Students

Beyond the Pandemic: The Interplay and Biological Effects of COVID-19 on Cancer Patients -A Mini Review

This article delves into the relationship between COVID-19 and cancer. The challenges and effects of the COVID-19 pandemic on cancer patients are highlighted, along with an explanation of the most crucial strategies that must be adhered to avoid this virus. Explaining the importance of healthcare systems in providing services to patients and assisting them to improve their health condition. This article concentrates on recent studies and clinical observations as it allows for an accurate and comprehensive understanding of the effects of this pandemic on cancer patients. The main issues will be focused on the impact of viral infections on cancerous tumours while clarifying the long-term consequences on patients’ lives. The main goal of this article is to inform healthcare workers, physicians, and researchers about the impact and seriousness of COVID-19 on cancer patients

From Pixels to Diagnoses: Deep Learning's Impact on Medical Image Processing-A Survey

In healthcare, medical image processing is considered one of the most significant procedures used in diagnosing pathological conditions. Magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and X-ray visualization have been used. Health institutions are seeking to use artificial intelligence techniques to develop medical image processing and reduce the burden on physicians and healthcare workers. Deep learning has occupied an important place in the healthcare field, supporting specialists in analysing and processing medical images. This article will present a comprehensive survey on the significance of deep learning in the areas of segmentation, classification, disease diagnosis, image generation, image transformation, and image enhancement. This survey seeks to provide an overview of the significance of deep learning in the early detection of diseases, studying tumor localization behaviors, predicting malignant diseases, and determining the suitable treatment for a patient. This article concluded that deep learning is of great significance in improving healthcare, enabling healthcare workers to make diagnoses quickly and more accurately, and improving patient outcomes by providing them with appropriate treatment strategies

Patients with Inflammatory Bowel Disease and the Higher Incidence of Clostridium Difficile Infection

This study aimed at analyzing the patients with inflammatory bowel disease and the higher incidence of clostridium difficile infection by emphasizing the theoretical review of studies discussing the  inflammatory bowel diseases (IBD), which include Crohn’s disease and ulcerative colitis. And by discussing the treatment of CDI in IBD patients, the diagnosis of CDI in IBD, and the risk factors for CDI in IBD. The study concluded that clinicians should be cautious about the chances of CDI in patients who have an exacerbation of IBD. At times the IBD flare cannot be differentiated from CDI requiring a high degree of clinical suspicion and vouching for early stool testing for toxin assay. When CDI in IBD are established primarily within two days of hospital admission it suggests that a good number of the infection was acquired before admission. CDI should, therefore, be suspected in differentiated diagnosis for intractable IBD patients, because many such patients need not present with a history of antibiotic exposure or hospital admission and may largely be receiving outpatient treatment

Waterpipe Nicotine Dependence and Depressive Symptoms among Adolescent Waterpipe and Dual Users

Background. Waterpipe nicotine dependence and its association with depressive symptoms and dual usage among adolescents are currently not examined in the literature. Adolescents are a vulnerable population that is susceptible to depression and initiation of tobacco use. We aim, in this novel study, to assess the association between depressive symptoms and waterpipe nicotine dependence among adolescents in Jordan, evaluate the association between waterpipe smoking status (waterpipe smoker vs. dual user) and waterpipe nicotine dependence, and assess the internal validity of the Waterpipe Nicotine Dependence Scale (WNDS). Method. A cross-sectional study among adolescents of grade 9th to 12th in Jordan was conducted through multistage cluster random sampling. The self-reported Arabic Youth Tobacco Use Composite Measure Questionnaire (YTUCM) was used to collect the surveys that include demographic information, smoking status, and the WNDS to assess waterpipe nicotine dependence and depressive symptoms. Multiple linear regression and the t-test were used to analyze the data. Findings. One thousand three hundred and three surveys were collected, of which 1082 were included in the study (443 males and 639 females). 64.9% of the sample were nontobacco users, while 20.1% were waterpipe- (WTP-) only smokers, 11.4% were dual users, and 3.7% were cigarettes-only users. After adjusting for weights, 66.6% were nonsmokers, 19.2% were WTP-only smokers, 10.2% were dual users, and 3.9% were cigarettes-only smokers. Using multiple linear regression, depressive symptoms were significantly associated with WTP nicotine dependence (β 0.618), upon adjusting for confounders. Furthermore, dual users were associated with higher WTP nicotine dependence (β 12.034) compared to WTP-only smokers after adjusting for confounders. Cronbach’s alpha for the WNDS was 0.955. Conclusions. Our study shows that there is a statistically significant association between depressive symptoms and WTP nicotine dependence and higher dependence among dual users compared to WTP-only smokers. The WNDS can be a useful tool to assess WTP nicotine dependence with high internal consistency. However, a longitudinal study is needed to further understand the association and temporality between the depressive symptoms and WTP nicotine dependence. Additionally, research is needed to shorten the WNDS while maintaining high internal consistency and assess the external validity of the WNDS and the short- and long-term consequences of dual usage

Clinical, radiological, and electroencephalographic features of HHV-6 encephalitis following hematopoietic stem cell transplantation

To study the clinical, radiological, electroencephalographic, and cerebrospinal fluid (CSF) features of Human Herpes Virus 6 (HHV-6) encephalitis in leukemia patients underwent allogeneic hematopoietic stem cell transplantation (HSCT). We retrospectively reviewed all leukemia patients who underwent allogeneic HSCT between January 2010 and December 2018. The clinical, radiological, electroencephalographic, and CSF features of those with HHV6 encephalitis were recorded. A total of five cases of HHV6 encephalitis were identified. Three patients had Chronic Myelogenous Leukemia, one had Chronic Lymphocytic Leukemia and one had Acute Lymphoblastic Leukemia. All of them presented a few months after transplantation with altered mental status. Comorbidities included pancytopenia, sepsis, graft versus host disease, and multi-organ failure. EEG showed focal seizures originating from temporal lobes in two patients, generalized or focal periodic discharges in three patients, focal slowing in two patients, and diffuse slowing in three patients. MRI brain showed T2/FLAIR hyper-intensities in four patients; two of them in bilateral temporal lobes, one in the thalamus/hypothalamus/brainstem/cerebellum/basal ganglia, and one in the periventricular areas. CSF showed pleocytosis, high protein, and positive HHV-6 PCR. Foscarnet was used as an anti-viral agent. Anti-epileptics used were phenytoin, levetiracetam, and valproic acid. Four patients died in a few months, whereas one recovered completely. HHV-6 encephalitis can add significant morbidity and mortality to leukemic patients following allogeneic HSCT. Patients present with typical clinical features of encephalitis. Salient EEG characteristics include periodic discharges or overt temporal lobe seizures. MRI findings are T2/FLAIR signal hyperintensities, mainly in the temporal lobes. •HHV-6 encephalitis is a fatal complication of allogeneic hematopoietic stem cell transplantation (HSCT).•Common features include confusion, fever, headache, and seizures.•EEG can show focal or generalized periodic discharges or overt temporal lobe seizures.•MRI may show temporal lobe hyperintensities and diffusion restriction.•Starting Foscarnet and antiepileptic drugs as early as post HSCT patients develop confusion is recommended

Has the Future Started? The Current Growth of Artificial Intelligence, Machine Learning, and Deep Learning

In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military. In these fields, the accurate prediction and analysis of data are crucial, regardless of how large the data are. However, using big data is confusing due to the rapid growth and massive development in public life, which requires a tremendous human effort in order to deal with such type of data and extract worthy information from it. Thus, the role of artificial intelligence begins in analyzing big data based on scientific techniques, especially in machine learning, whereby it can identify patterns of decision-making and reduce human intervention. In this regard, the significance role of artificial intelligence, machine learning and deep learning is growing rapidly. In this article, the authors decide to highlight these sciences by discussing how to develop and apply them in many decision-making domains. In addition, the influence of artificial intelligence in healthcare and the gains this science provides in the face of the COVID-19 pandemic are highlighted. This article concludes that these sciences have a significant impact, especially in healthcare, as well as the ability to grow and improve their methodology in decision-making. Additionally, artificial intelligence is a vital science, especially in the face of COVID-19

Use of Innovative SPECT Techniques in the Presurgical Evaluation of Patients with Nonlesional Extratemporal Drug-Resistant Epilepsy

Up to 30% of patients with epilepsy may not respond to antiepileptic drugs. Patients with drug-resistant epilepsy (DRE) should undergo evaluation for seizure onset zone (SOZ) localization to consider surgical treatment. Cases of drug-resistant nonlesional extratemporal lobe epilepsy (ETLE) pose the biggest challenge in localizing the SOZ and require multiple noninvasive diagnostic investigations before planning the intracranial monitoring (ICM) or direct resection. Ictal Single Photon Emission Computed Tomography (i-SPECT) is a unique functional diagnostic tool that assesses the SOZ using the localized hyperperfusion that occurs early in the seizure. Subtraction ictal SPECT coregistered to MRI (SISCOM), statistical ictal SPECT coregistered to MRI (STATISCOM), and PET interictal subtracted ictal SPECT coregistered with MRI (PISCOM) are innovative SPECT methods for the determination of the SOZ. This article comprehensively reviews SPECT and sheds light on its vital role in the presurgical evaluation of the nonlesional extratemporal DRE

Medical students’ relative immunity, or lack thereof, against COVID-19 emotional distress and psychological challenges; a descriptive study from Jordan [version 2; peer review: 2 approved, 1 approved with reservations]

Background: Emotional distress is a major impact of COVID-19 among not only the general public but also healthcare workers including medical students. This study aimed at describing self-reported changes in emotional reactions associated with COVID-19 among medical students in Jordan and to assessing the potential effect of social media utilization on emotional distress among this group. Methods: A cross-sectional design was utilized to collect data early on during the outbreak in Jordan. All medical students in Jordan were eligible to complete an online questionnaire assessing self-reported emotional reactions to COVID-19 that covered four main domains: negative emotion (anxiety, worry, depression, panic, loneliness, and nervousness), positive emotion (happiness, joy, and excitement), sleep disorders (insomnia, shallow sleep, nightmares, and insufficient sleep), and aggression (verbal argument and physical fighting). The frequency of social media utilization as a main source of COVID-19 information was also assessed. Results: 59.9% of participants were females, 64.9% were enrolled at the two major medical schools in Jordan, and 59.6% were in the pre-clinical stage (years). A significant proportion of participants self-reported increased negative emotional levels of anxiety (49.2%), worry (72.4%), depression (23.1%), panic (22.6%), and nervousness (38.2%) and decreased positive emotional levels of happiness (44.8%), joy (47.3%), and feelings of excitement (45.1%). Self-reported sleep disorders were not as common (less than 15% for any of the four items), while arguing with others was at 26.7%. Significant differences by gender and academic year were detected. Almost half of participants reported using social media as a main source of COVID-19 information “most/all-the-times” with a significant effect of such on reducing emotional distress. Conclusion: The results suggest a potential effect of COVID-19 on the emotional distress of medical students. Addressing and mitigating such effects is crucial. The potential buffering effect of social media should be further investigated