AIMC Topic: Radiography, Thoracic

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Improving Computer-Aided Thoracic Disease Diagnosis through Comparative Analysis Using Chest X-ray Images Taken at Different Times.

Sensors (Basel, Switzerland) Feb 24, 2024
Medical professionals in thoracic medicine routinely analyze chest X-ray images, often comparing pairs of images taken at different times to detect lesions or anomalies in patients. This research aims to design a computer-aided diagnosis system that ...
Neural Networks, Computer Algorithms Computers Deep Learning Radiography, Thoracic X-Rays Thoracic Diseases Humans
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Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).

European radiology Feb 22, 2024
PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation exposure. Beam shaping energy filters can optimize imaging properties at lower radiation dosages. The aim of this study is to investigate whether use o...
Radiography, Thoracic Lymphangioleiomyomatosis Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Adult Prospective Studies Humans Deep Learning Male Tomography, X-Ray Computed Algorithms Middle Aged Lung Neoplasms Female Silver
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Approximating Intermediate Feature Maps of Self-Supervised Convolution Neural Network to Learn Hard Positive Representations in Chest Radiography.

Journal of imaging informatics in medicine Feb 21, 2024
Recent advances in contrastive learning have significantly improved the performance of deep learning models. In contrastive learning of medical images, dealing with positive representation is sometimes difficult because some strong augmentation techn...
Neural Networks, Computer Deep Learning Radiography, Thoracic Humans
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Automated Detection of Pediatric Foreign Body Aspiration from Chest X-rays Using Machine Learning.

The Laryngoscope Feb 17, 2024
OBJECTIVE/HYPOTHESIS: Standard chest radiographs are a poor diagnostic tool for pediatric foreign body aspiration. Machine learning may improve upon the diagnostic capabilities of chest radiographs. The objective is to develop a machine learning algo...
Sensitivity and Specificity Male Infant Retrospective Studies Female Radiography, Thoracic Foreign Bodies Respiratory Aspiration Adolescent Child, Preschool Child Humans Machine Learning Algorithms
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Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.

Medical physics Feb 9, 2024
BACKGROUND: Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication, clinical adoption of the developed methodology still needs to be improved. To overcome this limitat...
Aged Radiography, Thoracic Male Middle Aged Deep Learning Privacy Datasets as Topic Prognosis Tomography, X-Ray Computed Female Humans COVID-19
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Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.

Journal of imaging informatics in medicine Feb 8, 2024
This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radiograph diagnosis. We adopted a deep learning algorithm to concurrently detect the presence of normal ...
Algorithms Female Adult Humans Radiologists Male Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Middle Aged Radiography, Thoracic Deep Learning
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Nonradiology Health Care Professionals Significantly Benefit From AI Assistance in Emergency-Related Chest Radiography Interpretation.

Chest Jan 29, 2024
BACKGROUND: Chest radiographs (CXRs) are still of crucial importance in primary diagnostics, but their interpretation poses difficulties at times.
Radiography, Thoracic Retrospective Studies Adult Clinical Competence Female ROC Curve Humans Male Aged Emergency Service, Hospital Middle Aged Artificial Intelligence
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Artificial Intelligence for the Detection of Pneumothorax on Chest Radiograph: Not yet the Panacea.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Jan 28, 2024
Artificial Intelligence Radiography, Thoracic Pneumothorax Humans
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COPD: artificial intelligence detects and quantifies anomalies on chest CT enabling prediction of disease severity.

European radiology Jan 23, 2024
Pulmonary Disease, Chronic Obstructive Humans Severity of Illness Index Artificial Intelligence Tomography, X-Ray Computed Radiography, Thoracic
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General-Purpose Large Language Models Versus a Domain-Specific Natural Language Processing Tool for Label Extraction From Chest Radiograph Reports.

AJR. American journal of roentgenology Jan 17, 2024
Radiology Information Systems Radiography, Thoracic Humans Natural Language Processing
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