[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 …
Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective
S Schalekamp, WM Klein, KG van Leeuwen - Pediatric Radiology, 2022 - Springer
Artificial intelligence (AI) applications for chest radiography and chest CT are among the
most developed applications in radiology. More than 40 certified AI products are available …
most developed applications in radiology. More than 40 certified AI products are available …
The effectiveness of deep learning vs. traditional methods for lung disease diagnosis using chest X-ray images: A systematic review
Recently, deep learning has proven to be a successful technique especially in medical
image analysis. This paper aims to highlight the importance of deep learning architectures in …
image analysis. This paper aims to highlight the importance of deep learning architectures in …
Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review
S Padash, MR Mohebbian, SJ Adams… - Pediatric …, 2022 - Springer
Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less
attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) …
attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) …
[PDF][PDF] Optimized ensemble of hybrid rnn-gan models for accurate and automated lung tumour detection from ct images
The early diagnosis and treatment of lung tumour, the primary cause of cancer-related
deaths globally, depend critically on the identification of lung tumours. In this approach, a …
deaths globally, depend critically on the identification of lung tumours. In this approach, a …
Review on pneumonia image detection: A machine learning approach
This paper surveys and examines how computer-aided techniques can be deployed in
detecting pneumonia. It also suggests a hybrid model that can effectively detect pneumonia …
detecting pneumonia. It also suggests a hybrid model that can effectively detect pneumonia …
Pediatrics in artificial intelligence era: a systematic review on challenges, opportunities, and explainability
Background The emergence of artificial intelligence (AI) tools such as ChatGPT and Bard is
disrupting a broad swathe of fields, including medicine. In pediatric medicine, AI is also …
disrupting a broad swathe of fields, including medicine. In pediatric medicine, AI is also …
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 …
Towards accurate point-of-care tests for tuberculosis in children
In childhood tuberculosis (TB), with an estimated 69% of missed cases in children under 5
years of age, the case detection gap is larger than in other age groups, mainly due to its …
years of age, the case detection gap is larger than in other age groups, mainly due to its …