Mohamed Yacin Sikkandar^1,*, K. Hemalatha², M. Subashree³, S. Srinivasan⁴, Seifedine Kadry^5,6,7, Jungeun Kim⁸, Keejun Han⁹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 873-889, 2023, DOI:10.32604/csse.2023.035730

Abstract Recently, COVID-19 has posed a challenging threat to researchers, scientists, healthcare professionals, and administrations over the globe, from its diagnosis to its treatment. The researchers are making persistent efforts to derive probable solutions for managing the pandemic in their areas. One of the widespread and effective ways to detect COVID-19 is to utilize radiological images comprising X-rays and computed tomography (CT) scans. At the same time, the recent advances in machine learning (ML) and deep learning (DL) models show promising results in medical imaging. Particularly, the convolutional neural network (CNN) model can be applied to identifying abnormalities on chest radiographs.… More >

Min Hyung Park¹, Dongyan Nan^2,3, Yerin Kim¹, Jang Hyun Kim^1,2,3,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 121-134, 2023, DOI:10.32604/csse.2023.033247

Abstract After the outbreak of COVID-19, the global economy entered a deep freeze. This observation is supported by the Volatility Index (VIX), which reflects the market risk expected by investors. In the current study, we predicted the VIX using variables obtained from the sentiment analysis of data on Twitter posts related to the keyword “COVID-19,” using a model integrating the bidirectional long-term memory (BiLSTM), autoregressive integrated moving average (ARIMA) algorithm, and generalized autoregressive conditional heteroskedasticity (GARCH) model. The Linguistic Inquiry and Word Count (LIWC) program and Valence Aware Dictionary for Sentiment Reasoning (VADER) model were utilized as sentiment analysis methods. The… More >

Anahita Ali^*, Santosh Kumar

International Journal of Mental Health Promotion, Vol.25, No.7, pp. 833-845, 2023, DOI:10.32604/ijmhp.2023.028799

Abstract Since the coronavirus pandemic, many factors led to the change in the mental well-being of hospital administrators and their staff. The pandemic negatively impacted the availability and capability of health professionals to deliver essential services and meet rising demand. Therefore, this study aimed to understand the perspective of hospital administrators about issues and challenges that negatively impacted their staff’s mental health and hospital administrators’ coping response to mitigate those challenges and issues. An exploratory qualitative study was conducted with 17 hospital administrators (superintendents, deputy superintendents, nursing in charge and hospital in charge) working in a government district hospital of Rajasthan… More > Graphic Abstract

Yoshikiyo Kanada^1,#, Shota Suzumura^1,2,#, Soichiro Koyama¹, Kazuya Takeda¹, Kenta Fujimura¹, Takuma Ii¹, Shigeo Tanabe¹, Hiroaki Sakurai^1,*

International Journal of Mental Health Promotion, Vol.25, No.7, pp. 855-861, 2023, DOI:10.32604/ijmhp.2023.028956

Abstract Mental health difficulties can impact students’ motivation, focus, and ability to communicate with others. Students attending medical universities are more likely to experience anxiety, depression, and other mood changes for the first time. However, no study has examined their prevalence among Japanese rehabilitation students. This study investigated the prevalence of anxiety among Japanese rehabilitation students and aimed to identify its predictors. A cross-sectional study was conducted among 148 first-year physical and occupational therapy students at a private medical university in Japan in June 2022. Data on sociodemographic and personal characteristics, such as gender, age, subject major, regular exercise, place of… More >

B. Ducrocq

Psycho-Oncologie, Vol.16, No.3, pp. 313-317, 2022, DOI:10.3166/pson-2022-0209

Abstract La pandémie de Covid-19 liée au virus SARSCoV-2 a imposé un confinement mondial des populations en mars 2020. Outre les effets sur la santé publique et la santé physique, la santé mentale et la santé sexuelle ont été impactées. Les projets personnels des individus ont été bouleversés avec un impact sur les projets de couple et notamment de parentalités. La sexualité des individus s’est adaptée, entraînant des changements importants liés à l’isolement et les incertitudes en lien avec la pandémie mondiale. More >

L. Amaadour, I. Lahrch, O. Siyouri, K. Oualla, Z. Benbrahim, S. Arifi, C. Aarab, S. El Fakir, N. Mellas

Psycho-Oncologie, Vol.17, No.1, pp. 38-43, 2023, DOI:10.3166/pson-2022-0221

Abstract Introduction: La Covid-19 constitue une cause de plusieurs affections mentales, notamment chez les patients atteints de cancer qui sont déjà considérés comme une population vulnérable. Ainsi, l’objectif de la présente étude était d’évaluer les troubles psychologiques des patients suivis pour une maladie tumorale maligne, sous traitement médical systémique, ayant eu une infection au SARS-CoV2 ; ainsi que les conséquences que ces troubles psychologiques peuvent avoir sur l’adhésion aux soins oncologiques.
Méthode: Il s’agit d’une étude transversale sur une période de quatre mois (pic de la pandémie) menée au département d’oncologie médicale du centre hospitalier universitaire Hassan-II de Fès, Maroc. Les… More >

Aoli Li^1,#, Yan You^1,2,#, Kunli Wu³, Huibin Shan⁴, Younglee Kim⁵, Qilian He^1,*

International Journal of Mental Health Promotion, Vol.25, No.6, pp. 783-797, 2023, DOI:10.32604/ijmhp.2023.026956

Abstract Objective: To explore the double psychosocial threats of the COVID-19 pandemic, targeted behavior toward Chinese Americans, and the correlates to their mental health. Methods: A quantitative, cross-sectional, and descriptive design was utilized by using a purposive convenience sample of 301 Chinese Americans over the age of 18 residing in the United States. Online data collection was conducted through the social media platform WeChat from April 8–21, 2021. Descriptive statistical analysis was used for the participants’ demographic characteristics, Multidimensional Scale of Perceived Social Support (MSPSS), Double Threat Situations, COVID-19 Racial Discrimination, and General Anxiety Disorder-7 (GAD-7). Stepwise logistic regression was conducted… More > Graphic Abstract

Asma Qaiser¹, Saman Hina¹, Abdul Karim Kazi^1,*, Saad Ahmed², Raheela Asif³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 73-90, 2023, DOI:10.32604/iasc.2023.036784

Abstract In the past few years, social media and online news platforms have played an essential role in distributing news content rapidly. Consequently. verification of the authenticity of news has become a major challenge. During the COVID-19 outbreak, misinformation and fake news were major sources of confusion and insecurity among the general public. In the first quarter of the year 2020, around 800 people died due to fake news relevant to COVID-19. The major goal of this research was to discover the best learning model for achieving high accuracy and performance. A novel case study of the Fake News Classification using… More >

Meilin Wu^1,2, Lianggui Tang^1,2,*, Qingda Zhang^1,2, Ke Yan^1,2

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 179-198, 2023, DOI:10.32604/iasc.2023.036684

Abstract As COVID-19 poses a major threat to people’s health and economy, there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently. In non-stationary time series forecasting jobs, there is frequently a hysteresis in the anticipated values relative to the real values. The multilayer deep-time convolutional network and a feature fusion network are combined in this paper’s proposal of an enhanced Multilayer Deep Time Convolutional Neural Network (MDTCNet) for COVID-19 prediction to address this problem. In particular, it is possible to record the deep features and temporal dependencies in uncertain time series, and the features may then… More >

Shroog Alshomrani^*, Muhammad Arif, Mohammed A. Al Ghamdi

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5717-5742, 2023, DOI:10.32604/cmc.2023.038059

Abstract Coronavirus has infected more than 753 million people, ranging in severity from one person to another, where more than six million infected people died worldwide. Computer-aided diagnostic (CAD) with artificial intelligence (AI) showed outstanding performance in effectively diagnosing this virus in real-time. Computed tomography is a complementary diagnostic tool to clarify the damage of COVID-19 in the lungs even before symptoms appear in patients. This paper conducts a systematic literature review of deep learning methods for classifying the segmentation of COVID-19 infection in the lungs. We used the methodology of systematic reviews and meta-analyses (PRISMA) flow method. This research aims… More >