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  1. 3761
    “…Radiologists should never forget that a Chest CT angiography in children is first and foremost a chest CT.…”
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    Non-cardiovascular findings on chest CT angiography in children with congenital heart disease: How important are they?
  2. 3762
    “…The results demonstrated that multifractality of chest CT images was increased with the increase in lung infection in patients. …”
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    Multifractal analysis of chest CT images of patients with the 2019 novel coronavirus disease (COVID-19)
  3. 3763
    “…Autopsy studies have also demonstrated the presence of microvascular thrombi in affected sections of lung, which may be associated with diabetes. Chest imaging using x-ray (CXR) and computed tomography (CT) of chest is used to diagnose, assess disease progression and severity in COVID-19. …”
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    Chest radiological finding of COVID-19 in patients with and without diabetes mellitus: Differences in imaging finding
  4. 3764
    “…BACKGROUND: Mesenchymal chondrosarcoma is a rare and aggressive bone tumor with few reports of primary tumor in the chest wall. CASE: We report a case of a 17‐year‐old male presenting with back pain and a posterior mediastinal mass. …”
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    Mesenchymal chondrosarcoma of the chest wall in an adolescent patient: A case report and brief review of the literature
  5. 3765
    “…Due to its widespread availability, chest-CT is commonly used to detect early pulmonary manifestations and for follow-ups. …”
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    Do submillisievert-chest CT protocols impact diagnostic quality in suspected COVID-19 patients?
  6. 3766
    “…Since the elementary convolutional neural networks have not performed fairly well in identifying atypical image types hence, we recommend a novel and completely automated framework with a deep learning approach for the recognition and classification of chronic pulmonary disorders (CPD) and COVID-pneumonia using Thoracic or Chest X-Ray (CXR) images. A novel three-step, completely automated, approach is presented that first extracts the region of interest from CXR images for preprocessing, and they are then used to detects infected lungs X-rays from the Normal ones. …”
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    Diagnosis of hypercritical chronic pulmonary disorders using dense convolutional network through chest radiography
  7. 3767
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    Re: Indiscriminate use of CT chest imaging during the COVID-19 pandemic. A reply
  8. 3768
    “…BACKGROUND: Patients hospitalized with COVID-19 often exhibit markers of a hypercoagulable state and have an increased incidence of VTE. In response, CHEST issued rapid clinical guidance regarding prevention of VTE. …”
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    Thromboprophylaxis in Patients With COVID-19: A Brief Update to the CHEST Guideline and Expert Panel Report
  9. 3769
    “…Deciding on the early discharge of low-risk patients with chest pain is still controversial in emergency care. …”
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    Early discharging patients with chest pain using EDACS-ADP and COMPASS-MI risk predictors
  10. 3770
    “…In this study, the prognostic value of adding quantitative chest computed tomography (CT) to a multiple biomarker approach was evaluated among 148 hospitalized patients with confirmed COVID-19. …”
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    Biomarker evaluation for prognostic stratification of patients with COVID-19: the added value of quantitative chest CT
  11. 3771
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    Higher frequency of new chest tumor diagnoses in emergency department due to the COVID-19 pandemic
  12. 3772
    “…As radiography images can recognize pneumonia infections, this research brings an accurate and automatic technique based on a deep residual network to analyze chest X-ray images to monitor COVID-19 and diagnose verified patients. …”
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    Deep Residual Neural Network for COVID-19 Detection from Chest X-ray Images
  13. 3773
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    Lung Ultrasound in Children with Cystic Fibrosis in Comparison with Chest Computed Tomography: A Feasibility Study
  14. 3774
    “…For this purpose, machine learning (ML) has emerged as a strong forecasting method for detecting COVID-19 from chest X-ray images. In this paper, we used a Deep Learning Method (DLM) to detect COVID-19 using chest X-ray (CXR) images. …”
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    An Efficient Deep Learning Model to Detect COVID-19 Using Chest X-ray Images
  15. 3775
    “…In the present study, we aimed to investigate the relationship between the clinical findings and abnormalities noted in the chest computed tomography (CT) of patients with SFTS. …”
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    Associations between Chest CT Abnormalities and Clinical Features in Patients with the Severe Fever with Thrombocytopenia Syndrome
  16. 3776
    “…Evaluation and quantification of COVID-19 lung abnormalities based on chest Computed Tomography (CT) images can help determining the disease stage, efficiently allocating limited healthcare resources, and making informed treatment decisions. …”
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    COVID-rate: an automated framework for segmentation of COVID-19 lesions from chest CT images
  17. 3777
    “…Furthermore, an algorithm was developed which reliably detects chest compression periods automatically without the time-consuming process of manual annotation. …”
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    A sliding-window based algorithm to determine the presence of chest compressions from acceleration data
  18. 3778
    Publicado 2022
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    Methylprednisolone/tocilizumab: Methicillin-sensitive Staphylococcus aureus costochondritis and chest wall abscess: case report
  19. 3779
    por Little, Brent P.
    Publicado 2021
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    Disease Severity Scoring for COVID-19: A Welcome (Semi)Quantitative Role for Chest Radiography
  20. 3780
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    The Impact of Tocilizumab on Radiological Changes Assessed by Quantitative Chest CT in Severe COVID-19 Patients
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