AI Medical Compendium Topic:
Lung

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Deep learning applied to lung ultrasound videos for scoring COVID-19 patients: A multicenter study.

The Journal of the Acoustical Society of America
In the current pandemic, lung ultrasound (LUS) played a useful role in evaluating patients affected by COVID-19. However, LUS remains limited to the visual inspection of ultrasound data, thus negatively affecting the reliability and reproducibility o...

Long-term and short-term outcomes of robot- versus video-assisted anatomic lung resection in lung cancer: a systematic review and meta-analysis.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: Minimally invasive thoracic surgery has evolved with the introduction of robotic platforms. This study aimed to compare the long-term and short-term outcomes of the robot-assisted thoracic surgery (RATS) and video-assisted thoracic surger...

An Insight of the First Community Infected COVID-19 Patient in Beijing by Imported Case: Role of Deep Learning-Assisted CT Diagnosis.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
In the era of coronavirus disease 2019 (COVID-19) pandemic, imported COVID-19 cases pose great challenges to many countries. Chest CT examination is considered to be complementary to nucleic acid test for COVID-19 detection and diagnosis. We report t...

The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.

Medicine
In 2020, the new type of coronal pneumonitis became a pandemic in the world, and has firstly been reported in Wuhan, China. Chest CT is a vital component in the diagnostic algorithm for patients with suspected or confirmed COVID-19 infection. Therefo...

FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.

[A deep learning-based lung nodule density classification and segmentation method and its effectiveness under different CT reconstruction algorithms].

Zhonghua yi xue za zhi
To evaluate the diagnostic value of the lung nodule classification and segmentation algorithm based on deep learning among different CT reconstruction algorithms. Chest CT of 363 patients from June 2019 to September 2019 in Radiology Department of ...

A machine-learning based approach to quantify fine crackles in the diagnosis of interstitial pneumonia: A proof-of-concept study.

Medicine
Fine crackles are frequently heard in patients with interstitial lung diseases (ILDs) and are known as the sensitive indicator for ILDs, although the objective method for analyzing respiratory sounds including fine crackles is not clinically availabl...

Analysis of segmentation of lung parenchyma based on deep learning methods.

Journal of X-ray science and technology
Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to detail...

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Advances in experimental medicine and biology
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into...

Temporal changes of quantitative CT findings from 102 patients with COVID-19 in Wuhan, China: A longitudinal study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Computed tomography (CT) imaging combined with artificial intelligence is important in the diagnosis and prognosis of lung diseases.