COVID-19 pandemic is representing a serious challenge to worldwide public health. Lung Ultrasonography (LUS) has been signaled as a potential useful tool in this pandemic contest either to intercept viral pneumonia or to foster alternative paths. LUS could be useful in determining early lung involvement suggestive or not of COVID-19 pneumonia and potentially plays a role in managing decisions for hospitalization in isolation or admission in general ward. In order to face pandemic, in a period in which a large number of emergency room accesses with suspicious symptoms are expected, physicians need a standardized ultrasonographic approach, fast educational processes in order to be able to recognize both suggestive and not suggestive echographic signs and shared algorithms for LUS role in early management of patients.
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http://dx.doi.org/10.1007/s40477-020-00501-7 | DOI Listing |
Sci Rep
December 2024
Department of Radiology, Veterans Health Service Medical Center, Seoul, Republic of Korea.
This study aimed to compare computed tomography (CT) findings between basaloid lung squamous cell carcinoma (SCC) and non-basaloid SCC. From July 2003 to April 2021, 39 patients with surgically proven basaloid SCC were identified. For comparison, 161 patients with surgically proven non-basaloid SCC from June 2018 to January 2019 were selected consecutively.
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December 2024
The Engineering & Technical College of Chengdu University of Technology, Xiaoba Road, Leshan, 614000, China.
Many conditions, such as pulmonary edema, bleeding, atelectasis or collapse, lung cancer, and shadow formation after radiotherapy or surgical changes, cause Lung Opacity. An unsupervised cross-domain Lung Opacity detection method is proposed to help surgeons quickly locate Lung Opacity without additional manual annotations. This study proposes a novel method based on adversarial learning to detect Lung Opacity on chest X-rays.
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December 2024
Department of Radiology, Stanford University, Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA, 94304, USA.
The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pediatric chest radiographs and to assess its diagnostic performance. Chest radiographs from patients under 19 years old, collected between March and November 2021, were divided into test and exploring sets. A commercial adult-oriented AI software was utilized to detect lung lesions, including pneumothorax, consolidation, nodule, and pleural effusion, using a standard operating point of 15%.
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December 2024
Department of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China.
Hormographiella aspergillata is a rare hyaline mold causing invasive fungal infection in humans, until the frequent use of antifungal prophylaxis in immunocompromised hosts. Due to the high mortality of H. aspergillata infection, early recognition and treatment are crucial.
View Article and Find Full Text PDFWe present a clinical observation of an 18-year-old female patient with congenital bronchiectasis combined with congenital cystic degeneration of the upper lobes of both lungs, Williams-Campbell syndrome, long-COVID, severe course. The patient was treated in infectious disease department (three times), with subsequent transfer to pulmonology department of Kursk Regional Multi-Purpose Clinical Hospital from 31.01.
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