Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance
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 …
radiologist achieve improved efficiency and accuracy in chest radiograph diagnosis. We …
Deep learning for chest radiograph diagnosis in the emergency department
Background The performance of a deep learning (DL) algorithm should be validated in
actual clinical situations, before its clinical implementation. Purpose To evaluate the …
actual clinical situations, before its clinical implementation. Purpose To evaluate the …
Role of an automated deep learning algorithm for reliable screening of abnormality in chest radiographs: a prospective multicenter quality improvement study
A Govindarajan, A Govindarajan, S Tanamala… - Diagnostics, 2022 - mdpi.com
In medical practice, chest X-rays are the most ubiquitous diagnostic imaging tests. However,
the current workload in extensive health care facilities and lack of well-trained radiologists is …
the current workload in extensive health care facilities and lack of well-trained radiologists is …
Can artificial intelligence reliably report chest x-rays?: Radiologist validation of an algorithm trained on 2.3 million x-rays
P Putha, M Tadepalli, B Reddy, T Raj… - arXiv preprint arXiv …, 2018 - arxiv.org
Background: Chest X-rays are the most commonly performed, cost-effective diagnostic
imaging tests ordered by physicians. A clinically validated AI system that can reliably …
imaging tests ordered by physicians. A clinically validated AI system that can reliably …
Performance of a deep learning CNN model for the automated detection of 13 common conditions on Chest X-rays
T Karthik, V Kasiraman, B Paski, K Gurram… - Authorea …, 2023 - techrxiv.org
Background and aims: Chest X-rays are widely used, non-invasive, cost effective imaging
tests. However, the complexity of interpretation and global shortage of radiologists have led …
tests. However, the complexity of interpretation and global shortage of radiologists have led …
[HTML][HTML] Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United …
AAM AlJasmi, H Ghonim, ME Fahmy, A Nair… - European Journal of …, 2024 - Elsevier
Abstract Background Chest radiographs (CXRs) are widely used to screen for infectious
diseases like tuberculosis and COVID-19 among migrants. At such high-volume settings …
diseases like tuberculosis and COVID-19 among migrants. At such high-volume settings …
Diagnosis of normal chest radiographs using an autonomous deep-learning algorithm
T Dyer, L Dillard, M Harrison, TN Morgan, R Tappouni… - Clinical radiology, 2021 - Elsevier
Aim To evaluate the suitability of a deep-learning (DL) algorithm for identifying normality as
a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an …
a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an …
Development and performance testing of a deep learning computer-aided diagnosis system for chest X-rays
G Gana, T Sibanda, T Madzorera, M Nhemachena… - 2022 - Eur Respiratory Soc
Background: Medical imaging is essential for the diagnosis of many pathologies such as
pneumonia, pneumothorax and lung cancer. Chest X-rays provide an accessible and cost …
pneumonia, pneumothorax and lung cancer. Chest X-rays provide an accessible and cost …
Lesion-aware convolutional neural network for chest radiograph classification
F Li, JX Shi, L Yan, YG Wang, XD Zhang, MS Jiang… - Clinical Radiology, 2021 - Elsevier
AIM To investigate the performance of a deep-learning approach termed lesion-aware
convolutional neural network (LACNN) to identify 14 different thoracic diseases on chest X …
convolutional neural network (LACNN) to identify 14 different thoracic diseases on chest X …
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
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 …
including tuberculosis and lung cancer, which affect millions of people worldwide each year …