AIMC Topic: Radiography
Clear Filters Showing 671 to 680 of 1088 articles
Artificial intelligence for thoracic radiology: from research tool to clinical practice.
The European respiratory journal
May 20, 2021
Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.
The European respiratory journal
May 20, 2021
We aimed to develop a deep learning algorithm detecting 10 common abnormalities (DLAD-10) on chest radiographs, and to evaluate its impact in diagnostic accuracy, timeliness of reporting and workflow efficacy.DLAD-10 was trained with 146 717 radiogra...
Current and emerging artificial intelligence applications for pediatric interventional radiology.
Pediatric radiology
May 12, 2021
Artificial intelligence in medicine can help improve the accuracy and efficiency of diagnostics, selection of therapies and prediction of outcomes. Machine learning describes a subset of artificial intelligence that utilizes algorithms that can learn...
Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.
Clinical radiology
May 11, 2021
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...
An incremental learning approach to automatically recognize pulmonary diseases from the multi-vendor chest radiographs.
Computers in biology and medicine
May 8, 2021
The human respiratory network is a vital system that provides oxygen supply and nourishment to the whole body. Pulmonary diseases can cause severe respiratory problems, leading to sudden death if not treated timely. Many researchers have utilized dee...
A Prospective Applicant's Outlook on Radiology in Light of Artificial Intelligence.
Journal of the American College of Radiology : JACR
May 4, 2021
Effect of AI Explanations on Human Perceptions of Patient-Facing AI-Powered Healthcare Systems.
Journal of medical systems
May 4, 2021
Ongoing research efforts have been examining how to utilize artificial intelligence technology to help healthcare consumers make sense of their clinical data, such as diagnostic radiology reports. How to promote the acceptance of such novel technolog...
Automatic prediction of left cardiac chamber enlargement from chest radiographs using convolutional neural network.
European radiology
May 3, 2021
OBJECTIVE: To develop deep learning-based cardiac chamber enlargement-detection algorithms for left atrial (DLCE-LAE) and ventricular enlargement (DLCE-LVE), on chest radiographs METHODS: For training and internal validation of DLCE-LAE and -LVE, 5,0...
Deep Convolutional Neural Networks as a Diagnostic Aid-A Step Toward Minimizing Undetected Scaphoid Fractures on Initial Hand Radiographs.
JAMA network open
May 3, 2021
Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.
JAMA network open
May 3, 2021
IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; untreated scaphoid fractures can lead to degenerative wrist arthritis and debilitating pain, detrime...
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