AIMC Topic: Lung

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Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.

The Lancet. Digital health Apr 20, 2021
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
Pleural Diseases Neural Networks, Computer Algorithms Retrospective Studies Female Aged Male Humans Area Under Curve Radiography Radiographic Image Interpretation, Computer-Assisted Datasets as Topic Radiography, Thoracic Pleural Cavity Deep Learning United States Respiratory Distress Syndrome Middle Aged Lung Hospitals
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Automated detection of pneumonia cases using deep transfer learning with paediatric chest X-ray images.

The British journal of radiology Apr 16, 2021
OBJECTIVE: Pneumonia is a lung infection and causes the inflammation of the small air sacs (Alveoli) in one or both lungs. Proper and faster diagnosis of pneumonia at an early stage is imperative for optimal patient care. Currently, chest X-ray is co...
Child, Preschool ROC Curve Pneumonia Radiographic Image Interpretation, Computer-Assisted Early Diagnosis Infant Lung Deep Learning Humans Reproducibility of Results
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A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images.

Scientific reports Apr 14, 2021
The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer (SCLC) is of crucial importance for determining optimum cancer treatment. Hematoxylin and Eos...
Deep Learning ROC Curve Lung Neoplasms Databases, Factual Carcinoma, Squamous Cell Lung Adenocarcinoma Area Under Curve Small Cell Lung Carcinoma Humans
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Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks.

European radiology Apr 13, 2021
OBJECTIVES: The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features ass...
Humans Neural Networks, Computer Artificial Intelligence Lung Neoplasms Neoplasm Invasiveness Retrospective Studies Tomography, X-Ray Computed Lung
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RPLS-Net: pulmonary lobe segmentation based on 3D fully convolutional networks and multi-task learning.

International journal of computer assisted radiology and surgery Apr 12, 2021
PURPOSE: The robust and automatic segmentation of the pulmonary lobe is vital to surgical planning and regional image analysis of pulmonary related diseases in real-time Computer Aided Diagnosis systems. While a number of studies have examined this i...
Neural Networks, Computer Tomography, X-Ray Computed Lung Humans Imaging, Three-Dimensional Image Processing, Computer-Assisted Lung Diseases
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Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.

Mycopathologia Apr 11, 2021
This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Give...
Tomography, X-Ray Computed Lung Lung Diseases, Fungal Humans Artificial Intelligence Machine Learning
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Detection of COVID-19 from CT Lung Scans Using Transfer Learning.

Computational intelligence and neuroscience Apr 8, 2021
This paper aims to investigate the use of transfer learning architectures in the detection of COVID-19 from CT lung scans. The study evaluates the performances of various transfer learning architectures, as well as the effects of the standard Histogr...
Lung Humans Image Processing, Computer-Assisted COVID-19 Machine Learning Diagnosis, Computer-Assisted Area Under Curve Tomography, X-Ray Computed ROC Curve Datasets as Topic SARS-CoV-2
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Contrast-Attentive Thoracic Disease Recognition With Dual-Weighting Graph Reasoning.

IEEE transactions on medical imaging Apr 1, 2021
Automatic thoracic disease diagnosis is a rising research topic in the medical imaging community, with many potential applications. However, the inconsistent appearances and high complexities of various lesions in chest X-rays currently hinder the de...
Radiography Attention Humans Thoracic Diseases Neural Networks, Computer Lung
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A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.

International journal of computer assisted radiology and surgery Mar 31, 2021
PURPOSE: In this study, we try to consider the most common type of total anomalous pulmonary venous connection and established a machine learning-based prediction model for postoperative pulmonary venous obstruction by using clinical data and CT imag...
Tomography, X-Ray Computed Lung Vascular Diseases Humans Logistic Models ROC Curve Neural Networks, Computer Pulmonary Veins Predictive Value of Tests Machine Learning Area Under Curve
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[Robot-Assisted Lung Surgery].

Zentralblatt fur Chirurgie Mar 30, 2021
Anatomical lung resection is the standard treatment for patients with early-stage lung cancer. The conventional surgical techniques are thoracotomy and video-assisted thoracic surgery, but new methods have been added as technology has developed. The ...
Pneumonectomy Thoracic Surgery, Video-Assisted Humans Lung Lung Neoplasms Robotics
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