AIMC Topic: Radiography

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Artificial Intelligence in Paediatric Tuberculosis.

Pediatric radiology Jan 28, 2023
Tuberculosis (TB) continues to be a leading cause of death in children despite global efforts focused on early diagnosis and interventions to limit the spread of the disease. This challenge has been made more complex in the context of the coronavirus...
Radiography Humans Diagnostic Imaging Diagnosis, Computer-Assisted Artificial Intelligence Tuberculosis Child
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Effect of Contrast Level and Image Format on a Deep Learning Algorithm for the Detection of Pneumothorax with Chest Radiography.

Journal of digital imaging Jan 25, 2023
Under the black-box nature in the deep learning model, it is uncertain how the change in contrast level and format affects the performance. We aimed to investigate the effect of contrast level and image format on the effectiveness of deep learning fo...
Retrospective Studies Humans Radiography Pneumothorax ROC Curve Algorithms Deep Learning Radiography, Thoracic
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Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation.

Critical care (London, England) Jan 25, 2023
BACKGROUND: Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the correct position of an endotracheal tube (ETT) relative to the carina. However, their interpretation is often challenging and requires substantial time ...
Trachea Intensive Care Units Intubation, Intratracheal Deep Learning Radiography Humans
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Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays.

Scientific reports Jan 25, 2023
Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in healthcare. However, the impact of AI-generated advice on physicians' decision-making is underexplored. In this study, physicians received X-rays with correct diagno...
Radiography Artificial Intelligence Physicians Radiologists Humans X-Rays
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Evaluation of the accuracy of fully automatic cephalometric analysis software with artificial intelligence algorithm.

Orthodontics & craniofacial research Jan 24, 2023
OBJECTIVE: The aim of this study is to evaluate whether fully automatic cephalometric analysis software with artificial intelligence algorithms is as accurate as non-automated cephalometric analysis software for clinical diagnosis and research.
Algorithms Retrospective Studies Reproducibility of Results Artificial Intelligence Software Radiography Cephalometry
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Artificial intelligence in radiology: trainees want more.

Clinical radiology Jan 19, 2023
AIM: To understand the attitudes of UK radiology trainees towards artificial intelligence (AI) in Radiology, in particular, assessing the demand for AI education.
Radiology Radiologists Humans Surveys and Questionnaires Artificial Intelligence Radiography
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Triaging: Another Vital Application of the Deep Learning Technique on Chest Radiographs at the Emergency Department.

Radiology Jan 17, 2023
Triage Radiography Chest Pain Emergency Service, Hospital Humans Deep Learning
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Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Radiology Jan 17, 2023
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS), pulmonary embolism (PE), or aortic dissection (AD), often yielding negative resu...
Male Middle Aged Retrospective Studies Female Radiography Chest Pain Acute Coronary Syndrome Deep Learning Triage Humans
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Deep learning-based prediction of mandibular growth trend in children with anterior crossbite using cephalometric radiographs.

BMC oral health Jan 17, 2023
BACKGROUND: It is difficult for orthodontists to accurately predict the growth trend of the mandible in children with anterior crossbite. This study aims to develop a deep learning model to automatically predict the mandibular growth result into norm...
Malocclusion Mandible Radiography Deep Learning Child Humans Neural Networks, Computer
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Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach.

Scientific reports Jan 17, 2023
Chest X-rays are the most economically viable diagnostic imaging test for active pulmonary tuberculosis screening despite the high sensitivity and low specificity when interpreted by clinicians or radiologists. Computer aided detection (CAD) algorith...
Tuberculosis, Pulmonary X-Rays Radiography Tuberculosis Humans Lung Deep Learning
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