Monkeypox- a menacing challenge or an endemic?

Fatima, Nabeela; Mandava, Kiranmai

doi:10.1016/j.amsu.2022.103979

Cited by 9 publications

(6 citation statements)

References 2 publications

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“…The mortality of MPX is generally higher for young adults, children, and immunocompromised individuals. It is like smallpox that MPX is generally more fatal for children than adults [9,25]. In humans, the MPXV infection starts with an incubation period, then a prodrome of fever, disseminated skin lesions (growing from macules to papules, vesicles, and pustules), and scabbing [31].…”

Section: Common Symptoms Complicationsmentioning

confidence: 99%

“…Between May 7 and 25, 2022, 86 cases of MPX infection were reported in the UK (79 cases being male and 66 cases being bisexual, gay, or other men who had sex with men) [7,8]. MPXV is an orthopoxviral, Chordopoxvirinae, and a close subgroup of variola viruses (smallpox) [9]. Smallpox is highly transmissible, and its mortality rate is approximately 30%.…”

Section: Introductionmentioning

confidence: 99%

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"Monkeypox: Re-Emerging Infectious Disease and One Health Strategy"

Wang

2024

BJSTR

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World Health Organization (WHO) has announced the monkeypox (MPX) epidemic as a global public health emergency due to its re-emergence, remarkable increase in the number of MPX cases worldwide, and its potential spread. This paper introduces the symptoms, complications, and features of MPX; its transmission, diagnosis and testing, vaccines, and treatment; MPX and sexually transmitted diseases, especially the human immunodeficiency virus (HIV); possible natural hosts or reservoirs of the monkeypox virus (MPXV). A useful tool for MPX and surgical safety recommendations are presented. The challenges in fighting the MPX epidemic, the One Health strategy, and future research are discussed.

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Section: Common Symptoms Complicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

"Monkeypox: Re-Emerging Infectious Disease and One Health Strategy"

Wang

2024

BJSTR

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“…After being exposed to something, a person may not have symptoms for days or weeks. Early monkeypox symptoms include those similar to the flu, such as fever, chills, headaches, aches, muscle pains, fatigue, and swollen lymph nodes ( Fatima & Mandava, 2022 ). After a few days, a rash will typically begin to appear.…”

Section: Introductionmentioning

confidence: 99%

MonkeyNet: A robust deep convolutional neural network for monkeypox disease detection and classification

Bala

Hossain

et al. 2023

Neural Networks

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“…Although the virus has been exceptionally prevalent since 1970, and the preponderance of cases was reported in regions of Central and West Africa [ 4 ]. In 2022, the outbreak of monkeypox was reiterated in the United Kingdom (UK), originating from a British resident with a Nigeria traveling history [ 5 ]. The monkeypox virus is predominant in 12 endemic states, as reported by the World Health Organization (WHO); nevertheless, occurrences of monkeypox have recently been confirmed in 12 non-endemic states [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Blockchain-enabled healthcare monitoring system for early Monkeypox detection

2023

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The recent emergence of monkeypox poses a life-threatening challenge to humans and has become one of the global health concerns after COVID-19. Currently, machine learning-based smart healthcare monitoring systems have demonstrated significant potential in image-based diagnosis including brain tumor identification and lung cancer diagnosis. In a similar fashion, the applications of machine learning can be utilized for the early identification of monkeypox cases. However, sharing critical health information with various actors such as patients, doctors, and other healthcare professionals in a secure manner remains a research challenge. Motivated by this fact, our paper presents a blockchain-enabled conceptual framework for the early detection and classification of monkeypox using transfer learning. The proposed framework is experimentally demonstrated in Python 3.9 using a monkeypox dataset of 1905 images obtained from the GitHub repository. To validate the effectiveness of the proposed model, various performance estimators, namely accuracy, recall, precision, and F1-score, are employed. The performance of different transfer learning models, namely Xception, VGG19, and VGG16, is compared against the presented methodology. Based on the comparison, it is evident that the proposed methodology effectively detects and classifies the monkeypox disease with a classification accuracy of 98.80%. In future, multiple skin diseases such as measles and chickenpox can be diagnosed using the proposed model on the skin lesion datasets.

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Monkeypox- a menacing challenge or an endemic?

Cited by 9 publications

References 2 publications

"Monkeypox: Re-Emerging Infectious Disease and One Health Strategy"

"Monkeypox: Re-Emerging Infectious Disease and One Health Strategy"

MonkeyNet: A robust deep convolutional neural network for monkeypox disease detection and classification

Blockchain-enabled healthcare monitoring system for early Monkeypox detection

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