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  • Open Access

    ARTICLE

    SARS-CoV2 et cancer : quel impact psychologique ?
    Expérience du service d’oncologie médicale du centre hospitalier universitaire Hassan-II de Fès, Maroc

    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 >

  • Open Access

    ARTICLE

    Semantic Pneumonia Segmentation and Classification for Covid-19 Using Deep Learning Network

    M. M. Lotfy1, Hazem M. El-Bakry2, M. M. Elgayar3, Shaker El-Sappagh4,5, G. Abdallah M. I1, A. A. Soliman1, Kyung Sup Kwak6,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1141-1158, 2022, DOI:10.32604/cmc.2022.024193

    Abstract Early detection of the Covid-19 disease is essential due to its higher rate of infection affecting tens of millions of people, and its high number of deaths also by 7%. For that purpose, a proposed model of several stages was developed. The first stage is optimizing the images using dynamic adaptive histogram equalization, performing a semantic segmentation using DeepLabv3Plus, then augmenting the data by flipping it horizontally, rotating it, then flipping it vertically. The second stage builds a custom convolutional neural network model using several pre-trained ImageNet. Finally, the model compares the pre-trained data to the new output, while repeatedly… More >

  • Open Access

    REVIEW

    Updated thoughts on SARS-CoV-2 and coronavirus therapies, fighting and surviving

    WENJUAN LI*, GE SONG

    BIOCELL, Vol.44, No.2, pp. 127-135, 2020, DOI:10.32604/biocell.2020.010018

    Abstract From late December 2019 a new human-adapted coronavirus, SARS-CoV-2, was observed and isolated in clustered patients in Wuhan, China. It has been proved to be able to transmit human-to-human and cause pneumonia, leading to about 2% fatality. Its genome characteristics, immune responses and related potential treatments, such as chemical drugs, serum transfusion and vaccines including DNA vaccines, are discussed in this review for a brief summary. More >

  • Open Access

    ARTICLE

    Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity

    Xiangao Jiang1, Megan Coffee2, 3, *, Anasse Bari4, *, Junzhang Wang4, Xinyue Jiang5, Jianping Huang1, Jichan Shi1, Jianyi Dai1, Jing Cai1, Tianxiao Zhang6, Zhengxing Wu1, Guiqing He1, Yitong Huang7

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691

    Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations… More >

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