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  • Open Access

    ARTICLE

    The IOMT-Based Risk-Free Approach to Lung Disorders Detection from Exhaled Breath Examination

    Mohsin Ghani, Ghulam Gilanie*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2835-2847, 2023, DOI:10.32604/iasc.2023.034857 - 15 March 2023

    Abstract The lungs are the main fundamental part of the human respiratory system and are among the major organs of the human body. Lung disorders, including Coronavirus (Covid-19), are among the world’s deadliest and most life-threatening diseases. Early and social distance-based detection and treatment can save lives as well as protect the rest of humanity. Even though X-rays or Computed Tomography (CT) scans are the imaging techniques to analyze lung-related disorders, medical practitioners still find it challenging to analyze and identify lung cancer from scanned images. unless COVID-19 reaches the lungs, it is unable to be… More >

  • Open Access

    ARTICLE

    COVID-19 Detection Based on 6-Layered Explainable Customized Convolutional Neural Network

    Jiaji Wang1,#, Shuwen Chen1,2,3,#,*, Yu Cao1,#, Huisheng Zhu1, Dimas Lima4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2595-2616, 2023, DOI:10.32604/cmes.2023.025804 - 09 March 2023

    Abstract This paper presents a 6-layer customized convolutional neural network model (6L-CNN) to rapidly screen out patients with COVID-19 infection in chest CT images. This model can effectively detect whether the target CT image contains images of pneumonia lesions. In this method, 6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample. The results show that the model improves the accuracy of screening out COVID-19 patients. Compared to other methods, the performance is better. In addition, the method can be extended to other More >

  • Open Access

    REVIEW

    Indian medicinal plants are effective in the treatment and management of COVID-19

    SUBHASH CHANDRA1,2, SANTWANA PALAI3, EDINARDO FAGNER FERREIRA-MATIAS4, IVO CAVALCANTE PITA-NETO4, CíCERO LUCAS GOMES-RAMALHO4, EDLANE MARTINS DE ANDRADE4, RAY SILVA DE ALMEIDA5, MARCELLO IRITI6,7,*, HENRIQUE DOUGLAS MELO-COUTINHO5,*

    BIOCELL, Vol.47, No.4, pp. 677-695, 2023, DOI:10.32604/biocell.2023.026081 - 08 March 2023

    Abstract Indian medicinal plants are referred to as the “nectar of life” owing to their phytochemicals and bioactive complexes that are beneficial in treating diseases. Coronavirus disease 2019 (COVID-19) is a global health issue without any proper medication. The indigenous plants of India can be exploited to control the precise signs of SARS-CoV-2. The Ministry of AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) has advised routine usage of medicinal plants for COVID-19. Medicinal plants like Zingiber officinalis, Azadirachta indica, Ocimum sanctum, Nigella sativa, Withania somnifera, Curcuma longa, Piper nigrum, Allium sativum, Tinospora cordifolia, etc. have More >

  • Open Access

    ARTICLE

    Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

    Heesup Han1, Hong Ngoc Nguyen2, Hyerin Lee3, Sanghyeop Lee4,*

    International Journal of Mental Health Promotion, Vol.25, No.4, pp. 449-469, 2023, DOI:10.32604/ijmhp.2023.025379 - 01 March 2023

    Abstract Since the outbreak of COVID-19, tourists have been increasingly concerned over various risks of international travel, while knowledge of the pandemic appears to vary significantly. In addition, as travel restrictions continue to impact adversely on international tourism, tourism efforts should be placed more on the domestic markets. Via structural equation modeling, this study unearthed different risk factors impacting Korean travelers’ choices of alternative local destinations in the post-pandemic era. In addition, this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19, which was proven to hold a significantly More >

  • Open Access

    ARTICLE

    The Impact of COVID-19 on the Mental-Emotional Wellbeing of Primary Healthcare Professionals: A Descriptive Correlational Study

    Regina Lai-Tong Lee1,2,*, Anson Chiu-Yan Tang3, Ho-Yu Cheng1, Connie Yuen-Yu Chong1, Wilson Wai-San Tam4, Wai-Tong Chien1, Sally Wai-Chi Chan5

    International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388 - 21 February 2023

    Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation… More >

  • Open Access

    ARTICLE

    Topic Models to Analyze Disaster-Related Newspaper Articles: Focusing on COVID-19

    Yun-Jung Choi1, Youn-Joo Um2,*

    International Journal of Mental Health Promotion, Vol.25, No.3, pp. 421-431, 2023, DOI:10.32604/ijmhp.2023.023255 - 21 February 2023

    Abstract Major media outlets have run many articles on the COVID-19 pandemic. Since the public suffers cognitive and emotional effects related to COVID-19 from such reports, we analyzed and reviewed the topics of news reports. We searched newspaper articles with the term ‘COVID-19’ term in four Korean daily newspapers from January 20, 2020, when the first patient in Korea was found, to June 15, 2020. Topic modeling analysis was conducted through text mining using R. Five themes were found: “Changes in people’s everyday life,” “Socio-economic shock,” “Trends in infection,” “Role of the government and business,” and More >

  • Open Access

    ARTICLE

    SRC: Superior Robustness of COVID-19 Detection from Noisy Cough Data Using GFCC

    Basanta Kumar Swain1, Mohammad Zubair Khan2,*, Chiranji Lal Chowdhary3, Abdullah Alsaeedi4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2337-2349, 2023, DOI:10.32604/csse.2023.036192 - 09 February 2023

    Abstract This research is focused on a highly effective and untapped feature called gammatone frequency cepstral coefficients (GFCC) for the detection of COVID-19 by using the nature-inspired meta-heuristic algorithm of deer hunting optimization and artificial neural network (DHO-ANN). The noisy crowdsourced cough datasets were collected from the public domain. This research work claimed that the GFCC yielded better results in terms of COVID-19 detection as compared to the widely used Mel-frequency cepstral coefficient in noisy crowdsourced speech corpora. The proposed algorithm's performance for detecting COVID-19 disease is rigorously validated using statistical measures, F1 score, confusion matrix, More >

  • Open Access

    ARTICLE

    Deep Learning Based Face Mask Detection in Religious Mass Gathering During COVID-19 Pandemic

    Abdullah S. AL-Malaise AL-Ghamdi1,2,3, Sultanah M. Alshammari3,4, Mahmoud Ragab3,5,6,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869 - 09 February 2023

    Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass… More >

  • Open Access

    ARTICLE

    A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

    Hicham Moujahid1, Bouchaib Cherradi1,2,*, Oussama El Gannour1, Wamda Nagmeldin3, Abdelzahir Abdelmaboud4, Mohammed Al-Sarem5,6, Lhoussain Bahatti1, Faisal Saeed7, Mohammed Hadwan8,9

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1789-1809, 2023, DOI:10.32604/csse.2023.034022 - 09 February 2023

    Abstract Due to the rapid propagation characteristic of the Coronavirus (COVID-19) disease, manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection. Despite, new automated diagnostic methods have been brought on board, particularly methods based on artificial intelligence using different medical data such as X-ray imaging. Thoracic imaging, for example, produces several image types that can be processed and analyzed by machine and deep learning methods. X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines. Through this paper,… More >

  • Open Access

    ARTICLE

    A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

    Mohammad Aslefallah1, Şuayip Yüzbaşi2, Saeid Abbasbandy1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1687-1706, 2023, DOI:10.32604/cmes.2023.025647 - 06 February 2023

    Abstract In this work, the exponential approximation is used for the numerical simulation of a nonlinear SITR model as a system of differential equations that shows the dynamics of the new coronavirus (COVID-19). The SITR mathematical model is divided into four classes using fractal parameters for COVID-19 dynamics, namely, susceptible (S), infected (I), treatment (T), and recovered (R). The main idea of the presented method is based on the matrix representations of the exponential functions and their derivatives using collocation points. To indicate the usefulness of this method, we employ it in some cases. For error More > Graphic Abstract

    A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

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