AIMC Topic: Radiography, Thoracic

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Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs.

JAMA network open Mar 1, 2019
IMPORTANCE: Interpretation of chest radiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chest radiographs may help streamline the clinical workflow.
Algorithms Female Reproducibility of Results Aged Humans Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Thoracic Diseases Adult Male Middle Aged
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Potential of a machine-learning model for dose optimization in CT quality assurance.

European radiology Feb 19, 2019
OBJECTIVES: To evaluate machine learning (ML) to detect chest CT examinations with dose optimization potential for quality assurance in a retrospective, cross-sectional study.
Humans Machine Learning Retrospective Studies Radiation Injuries Thoracic Diseases Male Middle Aged Adolescent Young Adult Radiography, Thoracic Multidetector Computed Tomography Adult Quality Assurance, Health Care Cross-Sectional Studies Female Radiation Dosage Aged Aged, 80 and over
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How far have we come? Artificial intelligence for chest radiograph interpretation.

Clinical radiology Jan 28, 2019
Due to recent advances in artificial intelligence, there is renewed interest in automating interpretation of imaging tests. Chest radiographs are particularly interesting due to many factors: relatively inexpensive equipment, importance to public hea...
Algorithms Forecasting Diagnosis, Computer-Assisted Radiography, Thoracic Humans Lung Diseases Artificial Intelligence Tuberculosis, Pulmonary Machine Learning
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Automated Triaging of Adult Chest Radiographs.

Radiology Jan 22, 2019
Neural Networks, Computer Adult Radiography, Thoracic Humans
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Learning to detect chest radiographs containing pulmonary lesions using visual attention networks.

Medical image analysis Jan 9, 2019
Machine learning approaches hold great potential for the automated detection of lung nodules on chest radiographs, but training algorithms requires very large amounts of manually annotated radiographs, which are difficult to obtain. The increasing av...
Humans Neural Networks, Computer Algorithms Diagnosis, Computer-Assisted Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted Lung Diseases Datasets as Topic
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A deep learning framework for unsupervised affine and deformable image registration.

Medical image analysis Dec 8, 2018
Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can b...
Heart Diseases Radiography, Thoracic Magnetic Resonance Imaging, Cine Humans Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Imaging, Three-Dimensional Unsupervised Machine Learning Tomography, X-Ray Computed
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A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...
Unified Medical Language System Radiography, Thoracic Natural Language Processing Area Under Curve Supervised Machine Learning Risk Factors Male Humans Respiratory Distress Syndrome Aged Middle Aged Electronic Health Records Length of Stay Adult Predictive Value of Tests Female Diagnosis, Computer-Assisted Cohort Studies
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Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

Artificial intelligence in medicine Nov 23, 2018
This paper explores cutting-edge deep learning methods for information extraction from medical imaging free text reports at a multi-institutional scale and compares them to the state-of-the-art domain-specific rule-based system - PEFinder and traditi...
Humans Neural Networks, Computer Radiography, Thoracic Deep Learning Pulmonary Embolism Information Storage and Retrieval
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Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study.

PLoS medicine Nov 20, 2018
BACKGROUND: Pneumothorax can precipitate a life-threatening emergency due to lung collapse and respiratory or circulatory distress. Pneumothorax is typically detected on chest X-ray; however, treatment is reliant on timely review of radiographs. Sinc...
Automation Radiography, Thoracic Pneumothorax Deep Learning Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Reproducibility of Results Diagnosis, Computer-Assisted Databases, Factual Prognosis Humans
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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.

PLoS medicine Nov 20, 2018
BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming task typically requires expert radiologis...
Reproducibility of Results Diagnosis, Computer-Assisted Humans Retrospective Studies Deep Learning Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Clinical Competence Radiologists Radiography, Thoracic Pneumonia
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