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A simple algorithm helps early identification of SARS-CoV-2 infection patients with severe progression tendency
A simple algorithm helps early identification of SARS-CoV-2 infection patients with severe progression tendency
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A simple algorithm helps early identification of SARS-CoV-2 infection patients with severe progression tendency

Infection, 2020-08, Vol.48 (4), p.577-584 [Peer Reviewed Journal]

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;2020. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.springernature.com/gp/researchers/campaigns/coronavirus ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0300-8126 ;EISSN: 1439-0973 ;DOI: 10.1007/s15010-020-01446-z ;PMID: 32440918

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2
An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension – an assessment of sick leave, presenteeism, and health care utilization
An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension – an assessment of sick leave, presenteeism, and health care utilization
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An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension – an assessment of sick leave, presenteeism, and health care utilization

Journal of headache and pain, 2024-05, Vol.25 (1), p.73-73 [Peer Reviewed Journal]

The Author(s) 2024 ;2024. The Author(s). ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1129-2369 ;EISSN: 1129-2377 ;DOI: 10.1186/s10194-024-01780-9 ;PMID: 38714920

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3
Clinical characteristics of 194 cases of COVID-19 in Huanggang and Taian, China
Clinical characteristics of 194 cases of COVID-19 in Huanggang and Taian, China
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Clinical characteristics of 194 cases of COVID-19 in Huanggang and Taian, China

Infection, 2020-10, Vol.48 (5), p.687-694 [Peer Reviewed Journal]

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;2020. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.springernature.com/gp/researchers/campaigns/coronavirus ;ISSN: 0300-8126 ;EISSN: 1439-0973 ;DOI: 10.1007/s15010-020-01440-5 ;PMID: 32390091

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4
Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy
Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy
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Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy

European radiology experimental, 2021-02, Vol.5 (1), p.7-7, Article 7 [Peer Reviewed Journal]

The Author(s) 2021 ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2509-9280 ;EISSN: 2509-9280 ;DOI: 10.1186/s41747-020-00203-z ;PMID: 33527198

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5
Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia
Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia
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Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia

Insights into imaging, 2021-04, Vol.12 (1), p.55-55, Article 55 [Peer Reviewed Journal]

The Author(s) 2021 ;COPYRIGHT 2021 Springer ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1869-4101 ;EISSN: 1869-4101 ;DOI: 10.1186/s13244-021-00998-4 ;PMID: 33913066

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6
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
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A deep learning approach for projection and body-side classification in musculoskeletal radiographs

European radiology experimental, 2024-02, Vol.8 (1), p.23-23 [Peer Reviewed Journal]

The Author(s) 2024 ;2024. The Author(s). ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2509-9280 ;DOI: 10.1186/s41747-023-00417-x ;PMID: 38353812

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7
Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study
Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study
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Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study

European radiology experimental, 2020-12, Vol.4 (1), p.68-68, Article 68 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2509-9280 ;EISSN: 2509-9280 ;DOI: 10.1186/s41747-020-00195-w ;PMID: 33319321

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8
Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches
Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches
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Artificial intelligence for differentiating COVID-19 from other viral pneumonias on CT: comparative analysis of different models based on quantitative and radiomic approaches

European radiology experimental, 2023-01, Vol.7 (1), p.3-3, Article 3 [Peer Reviewed Journal]

The Author(s) 2023 ;2023. The Author(s). ;The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2509-9280 ;EISSN: 2509-9280 ;DOI: 10.1186/s41747-022-00317-6 ;PMID: 36690869

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9
Association between thoracic and third lumbar CT-derived muscle mass and density in Caucasian patients without chronic disease: a proof-of-concept study
Association between thoracic and third lumbar CT-derived muscle mass and density in Caucasian patients without chronic disease: a proof-of-concept study
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Association between thoracic and third lumbar CT-derived muscle mass and density in Caucasian patients without chronic disease: a proof-of-concept study

European radiology experimental, 2023-05, Vol.7 (1), p.26-26 [Peer Reviewed Journal]

The Author(s) 2023 ;2023. The Author(s). ;The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2509-9280 ;DOI: 10.1186/s41747-023-00340-1 ;PMID: 37246199

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