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  1. 5561
    “…Partial breast reconstruction using chest wall perforator flaps (CWPF) is a recent option used by breast surgeons, mainly for lateral quadrant defects with a relatively large volume of excision. …”
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    Chest wall perforator flaps in partial breast reconstruction after breast conservation surgery: an additional oncoplastic surgical option
  2. 5562
    “…BACKGROUND: Computer-aided diagnosis on chest x-ray images using deep learning is a widely studied modality in medicine. …”
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    Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers
  3. 5563
    “…After extended lobectomy, a partial resection of the sixth to eighth ribs followed by chest wall reconstruction with Mersilene mesh and osteosynthesis for sixth and seventh rib was performed. …”
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    Reconstruction of the chest wall with a latissimus dorsi muscle flap after an infection of alloplastic material: a case report
  4. 5564
    “…Two district general hospital radiologists reviewed the chest CT images without prior knowledge of the RT-PCR test results. …”
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    Positive Chest CT Features in Patients With COVID-19 Pneumonia and Negative Real-Time Polymerase Chain Reaction Test
  5. 5565
    “…The study reveals that infected patients exhibit distinct radiographic visual characteristics along with fever, dry cough, fatigue, dyspnea, etc. Chest X-Ray (CXR) is one of the important, non-invasive clinical adjuncts that play an essential role in the detection of such visual responses associated with SARS-COV-2 infection. …”
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    Coronavirus disease (COVID-19) detection in Chest X-Ray images using majority voting based classifier ensemble
  6. 5566
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    Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network
  7. 5567
    “…This model is trained on a dataset publically available containing a combination of 219 COVID-19, 1341 normal and 1345 viral pneumonia chest x-ray images. The experimental results reveal that our CVDNet. …”
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    CVDNet: A novel deep learning architecture for detection of coronavirus (Covid-19) from chest x-ray images
  8. 5568
    “…Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. …”
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    Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
  9. 5569
    “…Twenty-five of 27 patients had abnormal chest CT, while 2 (7.4%) patients had normal chest CT. …”
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    Clinical and chest CT presentations from 27 patients with COVID-19 pneumonia in Mogadishu, Somalia: a descriptive study
  10. 5570
    “…Therefore, this study aimed to investigate changes in 1- and 2-month chest X-ray (CXR) findings after the treatment initiation and compared them according to the final diagnosis of tuberculosis or non-tuberculosis. …”
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    Changes in chest X-ray findings in 1- and 2-month group after treatment initiation for suspected pulmonary tuberculosis
  11. 5571
    “…AIM: Our aim was to examine the relationship between rescuers' anthropometric data and chest compression quality during paediatric resuscitation training. …”
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    Randomised simulation trial found an association between rescuers' height and weight and chest compression quality during paediatric resuscitation
  12. 5572
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    Chest CT-scan finding of asymptomatic COVID-19 pneumonia: a prospective 542 patients’ single center study
  13. 5573
    “…An 82‐year‐old man with untreated diabetes mellitus (DM) had anterior chest wall swelling and ulcers 2 years following blunt chest trauma. …”
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    Sternal osteomyelitis and infective endocarditis after old trivial chest trauma in untreated diabetes mellitus: A case report
  14. 5574
    “…INTRODUCTION: The COVID-19 pandemic has resulted in cancellation of medical peer meetings. The Chest Wall Injury Society Annual Summit was scheduled for April 2020. …”
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    Use of the Internet to Facilitate an Annual Scientific Meeting: A Report of the First Virtual Chest Wall Injury Society Summit
  15. 5575
    “…RT dose was 35 Gy/15 fractions/3 weeks to chest wall by two tangential fields and 40 Gy in same fractions to supraclavicular fossa (SCF) and internal mammary nodes (IMNs). …”
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    Late-term effects of hypofractionated chest wall and regional nodal radiotherapy with two-dimensional technique in patients with breast cancer
  16. 5576
    “…OBJECTIVE: This study aimed to use an automated deep convolution neural network based pre-trained transfer models for detection of COVID-19 infection in chest X-rays. MATERIAL AND METHODS: In a retrospective study, we have applied Visual Geometry Group (VGG)-16, VGG-19, MobileNet, and InceptionResNetV2 pre-trained models for detection COVID-19 infection from 348 chest X-ray images. …”
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    Transfer Learning-Based Automatic Detection of Coronavirus Disease 2019 (COVID-19) from Chest X-ray Images
  17. 5577
    “…To assess the use of a structured report in the Chest Computed Tomography (CT) reporting of patients with suspicious viral pneumonia by COVID-19 and the evaluation of the main CT patterns. …”
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    Coronavirus disease 2019 (COVID-19) in Italy: features on chest computed tomography using a structured report system
  18. 5578
    “…OBJECTIVE: Aimed to summarize the characteristics of chest CT imaging in Chinese hospitalized patients with Coronavirus Disease 2019 (COVID-19) to provide reliable evidence for further guiding clinical routine. …”
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    The chest CT features of coronavirus disease 2019 (COVID-19) in China: a meta-analysis of 19 retrospective studies
  19. 5579
    “…OBJECTIVE: In patients with mild COVID-19 pneumonia, chest high-resolution computed tomography (HRCT) is advised when risk factors for severe disease (i.e., age > 65 years and/or comorbidities) are present, and can influence management strategy. …”
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    Chest high-resolution computed tomography is associated to short-time progression to severe disease in patients with COVID-19 pneumonia
  20. 5580
    “…OBJECTIVES: We performed a systematic review and meta-analysis of the prevalence of chest CT findings in patients with confirmed COVID-19 infection. …”
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    Chest CT findings of coronavirus disease 2019 (COVID-19): A comprehensive meta-analysis of 9907 confirmed patients
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