AIMC Topic: Radiography, Thoracic
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CheXNet and feature pyramid network: a fusion deep learning architecture for multilabel chest X-Ray clinical diagnoses classification.
The international journal of cardiovascular imaging
Dec 27, 2023
The existing multilabel X-Ray image learning tasks generally contain much information on pathology co-occurrence and interdependency, which is very important for clinical diagnosis. However, the challenging part of this subject is to accurately diagn...
Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.
European radiology
Dec 19, 2023
OBJECTIVES: To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs.
Artificial Intelligence-Based Emphysema Quantification in Routine Chest Computed Tomography: Correlation With Spirometry and Visual Emphysema Grading.
Journal of computer assisted tomography
Dec 18, 2023
OBJECTIVE: The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysem...
Retrospectively assessing evaluation and management of artificial-intelligence detected nodules on uninterpreted chest radiographs in the era of radiologists shortage.
European journal of radiology
Nov 28, 2023
PURPOSE: High volumes of chest radiographs (CXR) remain uninterpreted due to severe shortage of radiologists. These CXRs may be informally reported by non-radiologist physicians, or not reviewed at all. Artificial intelligence (AI) software can aid l...
Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.
Scientific reports
Nov 13, 2023
In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB) with a customized multimodal approach and evaluated its performance in different clinical settings. Moreover, we investigated potential performance i...
A comprehensive segmentation of chest X-ray improves deep learning-based WHO radiologically confirmed pneumonia diagnosis in children.
European radiology
Nov 6, 2023
OBJECTIVES: To investigate a comprehensive segmentation of chest X-ray (CXR) in promoting deep learning-based World Health Organization's (WHO) radiologically confirmed pneumonia diagnosis in children.
MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.
Scientific reports
Oct 31, 2023
The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test have been demonstrated to have predictive value on Coronavirus Disease 2019 (COVID-19) diagnos...
An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs.
Scientific reports
Oct 9, 2023
The aim of this study was to develop and test an artificial intelligence (AI)-based algorithm for detecting common technical errors in canine thoracic radiography. The algorithm was trained using a database of thoracic radiographs from three veterina...
Deep Learning for Detection of Pneumothorax and Pleural Effusion on Chest Radiographs: Validation Against Computed Tomography, Impact on Resident Reading Time, and Interreader Concordance.
Journal of thoracic imaging
Sep 29, 2023
PURPOSE: To study the performance of artificial intelligence (AI) for detecting pleural pathology on chest radiographs (CXRs) using computed tomography as ground truth.
External validation of deep learning-based automated detection algorithm for chest radiograph: practical issues in outpatient clinic.
Acta radiologica (Stockholm, Sweden : 1987)
Sep 26, 2023
BACKGROUND: There have been no reports on diagnostic performance of deep learning-based automated detection (DLAD) for thoracic diseases in real-world outpatient clinic.
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