[HTML][HTML] Deep learning for chest X-ray analysis: A survey
E Çallı, E Sogancioglu, B van Ginneken… - Medical Image …, 2021 - Elsevier
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …
image analysis tasks. As the most commonly performed radiological exam, chest …
Deep learning for pneumothorax diagnosis: a systematic review and meta-analysis
T Sugibayashi, SL Walston… - European …, 2023 - Eur Respiratory Soc
Background Deep learning (DL), a subset of artificial intelligence (AI), has been applied to
pneumothorax diagnosis to aid physician diagnosis, but no meta-analysis has been …
pneumothorax diagnosis to aid physician diagnosis, but no meta-analysis has been …
Simplified transfer learning for chest radiography models using less data
Background Developing deep learning models for radiology requires large data sets and
substantial computational resources. Data set size limitations can be further exacerbated by …
substantial computational resources. Data set size limitations can be further exacerbated by …
[HTML][HTML] Use of artificial intelligence-based software as medical devices for chest radiography: a position paper from the Korean Society of Thoracic Radiology
Chest radiography (CR) is the primary examination for the evaluation and follow-up of
various thoracic diseases. The number of examinations is steadily on the increase, as is …
various thoracic diseases. The number of examinations is steadily on the increase, as is …
Machine learning-assisted high-throughput strategy for real-time detection of spermine using a triple-emission ratiometric probe
C Wu, P Tan, X Chen, H Chang, Y Chen… - … Applied Materials & …, 2023 - ACS Publications
In this study, we designed and fabricated a spermine-responsive triple-emission ratiometric
fluorescent probe using dual-emissive carbon nanoparticles and quantum dots, which …
fluorescent probe using dual-emissive carbon nanoparticles and quantum dots, which …
Artificial intelligence in paediatric tuberculosis
J Naidoo, SC Shelmerdine, CFU -Charcape… - Pediatric …, 2023 - Springer
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 …
focused on early diagnosis and interventions to limit the spread of the disease. This …
Machine learning augmented interpretation of chest X-rays: a systematic review
HK Ahmad, MR Milne, QD Buchlak, N Ektas… - Diagnostics, 2023 - mdpi.com
Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning
systems to assist clinicians and improve interpretation accuracy. An understanding of the …
systems to assist clinicians and improve interpretation accuracy. An understanding of the …
A 178-clinical-center experiment of integrating AI solutions for lung pathology diagnosis
In 2020, an experiment testing AI solutions for lung X-ray analysis on a multi-hospital
network was conducted. The multi-hospital network linked 178 Moscow state healthcare …
network was conducted. The multi-hospital network linked 178 Moscow state healthcare …
Database and AI diagnostic tools improve understanding of lung damage, correlation of pulmonary disease and brain damage in COVID-19
The COVID-19 pandemic caused a sharp increase in the interest in artificial intelligence (AI)
as a tool supporting the work of doctors in difficult conditions and providing early detection of …
as a tool supporting the work of doctors in difficult conditions and providing early detection of …
Image projective transformation rectification with synthetic data for smartphone-captured chest X-ray photos classification
Automatic interpretation of chest X-ray (CXR) photos taken by smartphones at the same
performance level as with digital CXRs is challenging, due to the projective transformation …
performance level as with digital CXRs is challenging, due to the projective transformation …