Pneumonia

A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.

The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Google scholar were used to search for AI studies. There were 15 studies of COVID-19 that used AI for ...

Anti-inflammatory and antibacterial activities of P. petiolosa (Christ) Ching ethyl acetate extract against S. aureus in mice.

P. petiolosa as a typical Chinese herbal medicine has been generally utilized as Chinese native medicine formulation for treatment of chronic bronchitis, bronchial asthma and pneumoconiosis. The objective of this study was to evaluate the anti-inflammatory and antibacterial activities of P. petiolosa ethyl acetate extract (PPEAE) against S. aureus in mice. The air-dried leaves were extracted with ...

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a C...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate sc...

A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.

Segmentation of pneumonia lesions from CT scans of COVID-19 patients is important for accurate diagnosis and follow-up. Deep learning has a potential ...

Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low ...

Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.

Automatic and accurate lung segmentation in chest X-ray (CXR) images is fundamental for computer-aided diagnosis systems since the lung is the region ...

Classifying Pneumonia among Chest X-Rays Using Transfer Learning.

Chest radiography has become the modality of choice for diagnosing pneumonia. However, analyzing chest X-ray images may be tedious, time-consuming and...

An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach.

Pneumonia is a severe health problem causing millions of deaths every year. The aim of this study was to develop an advanced deep learning-based archi...

[Machine learning-based method for interpreting the guidelines of the diagnosis and treatment of COVID-19].

The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short p...

Comparative outcomes of robot-assisted minimally invasive versus open esophagectomy in patients with esophageal squamous cell carcinoma: a propensity score-weighted analysis.

Robots are increasingly used in minimally invasive surgery. We evaluated the clinical benefits of robot-assisted minimally invasive esophagectomy (RAM...

Deep Learning Localization of Pneumonia: 2019 Coronavirus (COVID-19) Outbreak.

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks.

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines a...

Text mining meets community curation: a newly designed curation platform to improve author experience and participation at WormBase.

Biological knowledgebases rely on expert biocuration of the research literature to maintain up-to-date collections of data organized in machine-readab...

Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases.

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population ...

Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.

Ensuring correct radiograph view labeling is important for machine learning algorithm development and quality control of studies obtained from multipl...

Lung Segmentation on HRCT and Volumetric CT for Diffuse Interstitial Lung Disease Using Deep Convolutional Neural Networks.

A robust lung segmentation method using a deep convolutional neural network (CNN) was developed and evaluated on high-resolution computed tomography (...

Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.

Our objective is to evaluate the effectiveness of efficient convolutional neural networks (CNNs) for abnormality detection in chest radiographs and in...

Assessment of an ensemble of machine learning models toward abnormality detection in chest radiographs.

Respiratory diseases account for a significant proportion of deaths and disabilities across the world. Chest X-ray (CXR) analysis remains a common dia...

Attention-Guided Convolutional Neural Network for Detecting Pneumonia on Chest X-Rays.

Pneumonia is a common infectious disease in the world. Its main diagnostic method is chest X-ray (CXR) examination. However, the high visual similarit...