Imaging of Emerging Infectious Diseases

Jardon, Meghan; Mohammad, Shaden F.; Jude, Cecilia Matilda; Pahwa, Anokh

doi:10.1007/s40134-019-0338-4

Cited by 6 publications

(5 citation statements)

References 52 publications

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“…Specifically, CNN classification is applied in medical diagnosis to analyse and extract efficient features from images as an AI healthcare tool ( Sarvamangala and Kulkarni, 2021 ). Imaging radiology techniques for early diagnosis and treatment of emerging infectious diseases such as Zika, Ebola, or Chikungunya are other image analysis applications ( Jardon et al, 2019 ). Microscope image analysis using a U-Net (convolutional network architecture) to segment and detect Leishmaniosis ( Górriz et al, 2018 ) is a representative study of the wide variety of possibilities of CNNs.…”

Section: Novel Diagnostic Tools By Using Image Analysis Techniquesmentioning

confidence: 99%

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Maturana

Oliveira²,

Nadal³

et al. 2022

Front. Microbiol.

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Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a time-consuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for image detection of the malaria parasites emulate the microscopy visualization of an expert. Microscope automation provides a fast and low-cost diagnosis, requiring less supervision. Smartphones are a suitable option for microscopic diagnosis, allowing image capture and software identification of parasites. In addition, image analysis techniques could be a fast and optimal solution for the diagnosis of malaria, tuberculosis, or Neglected Tropical Diseases in endemic areas with low resources. The implementation of automated diagnosis by using smartphone applications and new digital imaging technologies in low-income areas is a challenge to achieve. Moreover, automating the movement of the microscope slide and image autofocusing of the samples by hardware implementation would systemize the procedure. These new diagnostic tools would join the global effort to fight against pandemic malaria and other infectious and poverty-related diseases.

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Section: Novel Diagnostic Tools By Using Image Analysis Techniquesmentioning

confidence: 99%

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Maturana

Oliveira²,

Nadal³

et al. 2022

Front. Microbiol.

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“…Disease was more fatal in the elderly, with a mortality rate of greater than 40% in patients over 60 years of age. Since 2004, no more infections have been detected, and the SARS pandemic was declared to be ended [ 99 ].…”

Section: Virusesmentioning

confidence: 99%

“…‘‘Suspected’’ SARS was defined with symptoms such as high fever and difficulty in breathing/cough. ‘‘Probable’’ SARS was defined as a suspected SARS with respiratory distress syndrome (RDS) or severe pneumonia [ 99 ]. Characteristic symptoms of MERS include fever, cough, and shortness of breath.…”

Section: Virusesmentioning

confidence: 99%

Comparative overview of emerging RNA viruses: Epidemiology, pathogenesis, diagnosis and current treatment

Chakrabartty

Khan

Mahanta³

et al. 2022

Annals of Medicine &Amp; Surgery

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“…Computed tomography (CT) is important in the diagnosis and monitoring of emerging infectious diseases caused by viral infections and manifested mainly in the respiratory tract [such as H1N1 and severe acute respiratory syndrome (SARS)] [ 1 , 2 ]. COVID-19 is a clinical infectious disease resulting in bilateral pneumonia and rapid deterioration of lung function [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19

et al. 2021

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This study investigated associations between chest computed tomography (CT) pulmonary opacity score on admission and clinical features and outcomes in COVID-19 patients. The retrospective multi-center cohort study included 496 COVID-19 patients in Jiangsu province, China diagnosed as of March 15, 2020. Patients were divided into four groups based on the quartile of pulmonary opacity score: ≤ 5%, 6–20%, 21–40% and 41% +. CT pulmonary opacity score was independently associated with age, single onset, fever, cough, peripheral capillary oxygen saturation, lymphocyte count, platelet count, albumin level, C-reactive protein (CRP) level and fibrinogen level on admission. Patients with score ≥ 41% had a dramatic increased risk of severe or critical illness [odds ratio (OR), 15.58, 95% confidence interval (CI) 3.82–63.53), intensive care unit (ICU)] admission (OR, 6.26, 95% CI 2.15–18.23), respiratory failure (OR, 19.49, 95% CI 4.55–83.40), and a prolonged hospital stay (coefficient, 2.59, 95% CI 0.46–4.72) compared to those with score ≤ 5%. CT pulmonary opacity score on admission, especially when ≥ 41%, was closely related to some clinical characteristics and was an independent predictor of disease severity, ICU admission, respiratory failure and long hospital stay in patients with COVID-19.

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Imaging of Emerging Infectious Diseases

Cited by 6 publications

References 52 publications

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review

Comparative overview of emerging RNA viruses: Epidemiology, pathogenesis, diagnosis and current treatment

Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19

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