GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 17, No. 18 ( 2020-09-08), p. 6530-
    Abstract: COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed health services in the most affected countries. In response, governments initiated a series of non-pharmaceutical interventions (NPIs) that led to severe economic and social impacts. The effect of these intervention measures on the spread of the COVID-19 pandemic are not well investigated within developing country settings. This study simulated the trajectories of the COVID-19 pandemic curve in Jordan between February and May and assessed the effect of Jordan’s strict NPI measures on the spread of COVID-19. A modified susceptible, exposed, infected, and recovered (SEIR) epidemic model was utilized. The compartments in the proposed model categorized the Jordanian population into six deterministic compartments: suspected, exposed, infectious pre-symptomatic, infectious with mild symptoms, infectious with moderate to severe symptoms, and recovered. The GLEAMviz client simulator was used to run the simulation model. Epidemic curves were plotted for estimated COVID-19 cases in the simulation model, and compared against the reported cases. The simulation model estimated the highest number of total daily new COVID-19 cases, in the pre-symptomatic compartmental state, to be 65 cases, with an epidemic curve growing to its peak in 49 days and terminating in a duration of 83 days, and a total simulated cumulative case count of 1048 cases. The curve representing the number of actual reported cases in Jordan showed a good pattern compatibility to that in the mild and moderate to severe compartmental states. The reproduction number under the NPIs was reduced from 5.6 to less than one. NPIs in Jordan seem to be effective in controlling the COVID-19 epidemic and reducing the reproduction rate. Early strict intervention measures showed evidence of containing and suppressing the disease.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    In: Universal Access in the Information Society, Springer Science and Business Media LLC
    Type of Medium: Online Resource
    ISSN: 1615-5289 , 1615-5297
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2039113-4
    SSG: 24,1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    In: Journal of Medical Internet Research, JMIR Publications Inc., Vol. 23, No. 2 ( 2021-2-9), p. e23467-
    Abstract: Many countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting. Objective The goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review. Methods This research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed. Results This study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps. Conclusions This article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.
    Type of Medium: Online Resource
    ISSN: 1438-8871
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2021
    detail.hit.zdb_id: 2028830-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Future Internet Vol. 13, No. 1 ( 2021-01-16), p. 19-
    In: Future Internet, MDPI AG, Vol. 13, No. 1 ( 2021-01-16), p. 19-
    Abstract: Social media sites are considered one of the most important sources of data in many fields, such as health, education, and politics. While surveys provide explicit answers to specific questions, posts in social media have the same answers implicitly occurring in the text. This research aims to develop a method for extracting implicit answers from large tweet collections, and to demonstrate this method for an important concern: the problem of heart attacks. The approach is to collect tweets containing “heart attack” and then select from those the ones with useful information. Informational tweets are those which express real heart attack issues, e.g., “Yesterday morning, my grandfather had a heart attack while he was walking around the garden.” On the other hand, there are non-informational tweets such as “Dropped my iPhone for the first time and almost had a heart attack.” The starting point was to manually classify around 7000 tweets as either informational (11%) or non-informational (89%), thus yielding a labeled dataset to use in devising a machine learning classifier that can be applied to our large collection of over 20 million tweets. Tweets were cleaned and converted to a vector representation, suitable to be fed into different machine-learning algorithms: Deep neural networks, support vector machine (SVM), J48 decision tree and naïve Bayes. Our experimentation aimed to find the best algorithm to use to build a high-quality classifier. This involved splitting the labeled dataset, with 2/3 used to train the classifier and 1/3 used for evaluation besides cross-validation methods. The deep neural network (DNN) classifier obtained the highest accuracy (95.2%). In addition, it obtained the highest F1-scores with (73.6%) and (97.4%) for informational and non-informational classes, respectively.
    Type of Medium: Online Resource
    ISSN: 1999-5903
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518385-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 5
    In: Medicina, MDPI AG, Vol. 58, No. 2 ( 2022-01-27), p. 198-
    Abstract: Background and Objectives: Sarcomas are rare malignant tumors of mesenchymal origin. Their low prevalence and histological heterogeneity make their diagnosis a challenging task. To the best of our knowledge, the epidemiology of soft tissue sarcomas (STSs) was not well studied in Jordan. This study thus aimed to determine STS epidemiologic trends at King Abdullah University Hospital (KAUH); a tertiary hospital that provides cancer healthcare for 70% of the population in Irbid Governorate, North Jordan. The findings of this study will provide a good reference point of the burden of STSs in Jordan and the Middle East region. Materials and Methods: All cases with confirmed STS diagnoses who attended KAUH from January 2003 until December 2018 were included in the initial analysis. Bone sarcomas, gastrointestinal stromal tumors and uterine sarcomas were not included in the study. Information collected from the pathology reports and electronic medical records was used to determine STS prevalence, incidence rate, age and gender distributions, histological types and anatomic location. Cases were reviewed by three pathologists with interest in soft tissue tumors. The findings were compared with literature. Results: In total, 157 STS cases were reported (1.9% of cancers diagnosed at KAUH during the 16-year study period). Crude annual incidence rate (IR) per 100,000 person-years ranged from 0.48 in 2015 to 1.83 in 2011 (average = 1.04). Age-standardized IR (ASR)(World WHO 2000–2025) was 1.37. Male:female ratio was 1.3:1. Median age was 39 years. Age ranged from 〈 1 year to 90 years. Overall STS rates increased with age. The most common histological types were liposarcoma (19%), rhabdomyosarcoma (17%) and leiomyosarcoma (10%). The most common anatomic location was the extremity (40.1%), followed by the trunk (14.7%), then head and neck (10.8%). Conclusion: STSs are rare in North Jordan. A slight increase in their incidence was identified during the study period similar to global trends. The collection of relevant data on established risk factors along with a broader scale evaluation of the epidemiology of STS in the Middle East region is recommended to better evaluate disease burden and trends.
    Type of Medium: Online Resource
    ISSN: 1648-9144
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2088820-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 7 ( 2020-12-3)
    Abstract: Background and Objective: Coronavirus disease 2019 (COVID-19) characterized by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created serious concerns about its potential adverse effects. There are limited data on clinical, radiological, and neonatal outcomes of pregnant women with COVID-19 pneumonia. This study aimed to assess clinical manifestations and neonatal outcomes of pregnant women with COVID-19. Methods: We conducted a systematic article search of PubMed, EMBASE, Scopus, Google Scholar, and Web of Science for studies that discussed pregnant patients with confirmed COVID-19 between January 1, 2020, and April 20, 2020, with no restriction on language. Articles were independently evaluated by two expert authors. We included all retrospective studies that reported the clinical features and outcomes of pregnant patients with COVID-19. Results: Forty-seven articles were assessed for eligibility; 13 articles met the inclusion criteria for the systematic review. Data is reported for 235 pregnant women with COVID-19. The age range of patients was 25–40 years, and the gestational age ranged from 8 to 40 weeks plus 6 days. Clinical characteristics were fever [138/235 (58.72%)], cough [111/235 (47.23%)] , and sore throat [21/235 (8.93%)]. One hundred fifty six out of 235 (66.38%) pregnant women had cesarean section, and 79 (33.62%) had a vaginal delivery. All the patients showed lung abnormalities in CT scan images, and none of the patients died. Neutrophil cell count, C-reactive protein (CRP) concentration, ALT, and AST were increased but lymphocyte count and albumin levels were decreased. Amniotic fluid, neonatal throat swab, and breastmilk samples were taken to test for SARS-CoV-2 but all found negativ results. Recent published evidence showed the possibility of vertical transmission up to 30%, and neonatal death up to 2.5%. Pre-eclampsia, fetal distress, PROM, pre-mature delivery were the major complications of pregnant women with COVID-19. Conclusions: Our study findings show that the clinical, laboratory and radiological characteristics of pregnant women with COVID-19 were similar to those of the general populations. The possibility of vertical transmission cannot be ignored but C-section should not be routinely recommended anymore according to latest evidences and, in any case, decisions should be taken after proper discussion with the family. Future studies are needed to confirm or refute these findings with a larger number of sample sizes and a long-term follow-up period.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2020
    detail.hit.zdb_id: 2775999-4
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    In: Healthcare, MDPI AG, Vol. 9, No. 4 ( 2021-04-09), p. 441-
    Abstract: The application of artificial intelligence (AI) to health has increased, including to COVID-19. This study aimed to provide a clear overview of COVID-19-related AI publication trends using longitudinal bibliometric analysis. A systematic literature search was conducted on the Web of Science for English language peer-reviewed articles related to AI application to COVID-19. A search strategy was developed to collect relevant articles and extracted bibliographic information (e.g., country, research area, sources, and author). VOSviewer (Leiden University) and Bibliometrix (R package) were used to visualize the co-occurrence networks of authors, sources, countries, institutions, global collaborations, citations, co-citations, and keywords. We included 729 research articles on the application of AI to COVID-19 published between 2020 and 2021. PLOS One (33/729, 4.52%), Chaos Solution Fractals (29/729, 3.97%), and Journal of Medical Internet Research (29/729, 3.97%) were the most common journals publishing these articles. The Republic of China (190/729, 26.06%), the USA (173/729, 23.73%), and India (92/729, 12.62%) were the most prolific countries of origin. The Huazhong University of Science and Technology, Wuhan University, and the Chinese Academy of Sciences were the most productive institutions. This is the first study to show a comprehensive picture of the global efforts to address COVID-19 using AI. The findings of this study also provide insights and research directions for academic researchers, policymakers, and healthcare practitioners who wish to collaborate in these domains in the future.
    Type of Medium: Online Resource
    ISSN: 2227-9032
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2721009-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 8
    Online Resource
    Online Resource
    Informa UK Limited ; 2022
    In:  Disability and Rehabilitation: Assistive Technology Vol. 17, No. 2 ( 2022-02-17), p. 159-165
    In: Disability and Rehabilitation: Assistive Technology, Informa UK Limited, Vol. 17, No. 2 ( 2022-02-17), p. 159-165
    Type of Medium: Online Resource
    ISSN: 1748-3107 , 1748-3115
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2234110-9
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 9
    Online Resource
    Online Resource
    JMIR Publications Inc. ; 2019
    In:  JMIR Rehabilitation and Assistive Technologies Vol. 6, No. 2 ( 2019-9-8), p. e12010-
    In: JMIR Rehabilitation and Assistive Technologies, JMIR Publications Inc., Vol. 6, No. 2 ( 2019-9-8), p. e12010-
    Abstract: Robot-assisted therapy has become a promising technology in the field of rehabilitation for poststroke patients with motor disorders. Motivation during the rehabilitation process is a top priority for most stroke survivors. With current advancements in technology there has been the introduction of virtual reality (VR), augmented reality (AR), customizable games, or a combination thereof, that aid robotic therapy in retaining, or increasing the interests of, patients so they keep performing their exercises. However, there are gaps in the evidence regarding the transition from clinical rehabilitation to home-based therapy which calls for an updated synthesis of the literature that showcases this trend. The present review proposes a categorization of these studies according to technologies used, and details research in both upper limb and lower limb applications. Objective The goal of this work was to review the practices and technologies implemented in the rehabilitation of poststroke patients. It aims to assess the effectiveness of exoskeleton robotics in conjunction with any of the three technologies (VR, AR, or gamification) in improving activity and participation in poststroke survivors. Methods A systematic search of the literature on exoskeleton robotics applied with any of the three technologies of interest (VR, AR, or gamification) was performed in the following databases: MEDLINE, EMBASE, Science Direct & The Cochrane Library. Exoskeleton-based studies that did not include any VR, AR or gamification elements were excluded, but publications from the years 2010 to 2017 were included. Results in the form of improvements in the patients’ condition were also recorded and taken into consideration in determining the effectiveness of any of the therapies on the patients. Results Thirty studies were identified based on the inclusion criteria, and this included randomized controlled trials as well as exploratory research pieces. There were a total of about 385 participants across the various studies. The use of technologies such as VR-, AR-, or gamification-based exoskeletons could fill the transition from the clinic to a home-based setting. Our analysis showed that there were general improvements in the motor function of patients using the novel interfacing techniques with exoskeletons. This categorization of studies helps with understanding the scope of rehabilitation therapies that can be successfully arranged for home-based rehabilitation. Conclusions Future studies are necessary to explore various types of customizable games required to retain or increase the motivation of patients going through the individual therapies.
    Type of Medium: Online Resource
    ISSN: 2369-2529
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2019
    detail.hit.zdb_id: 2798120-4
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 10
    Online Resource
    Online Resource
    MDPI AG ; 2020
    In:  International Journal of Environmental Research and Public Health Vol. 17, No. 15 ( 2020-08-02), p. 5574-
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 17, No. 15 ( 2020-08-02), p. 5574-
    Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...