The increasing complexity of diagnostic imaging often leads to misinterpretations and diagnostic errors, particularly in critical conditions such as pneumothorax. This study addresses the pressing need for improved diagnostic accuracy in CT scans by ...
BACKGROUND: Lung ultrasound can evaluate for pneumothorax but the accuracy of diagnosis depends on experience among physicians. This study aimed to investigate the sensitivity and specificity of intelligent lung ultrasound in comparison with chest x-...
The trend in the medical field is towards intelligent detection-based medical diagnostic systems. However, these methods are often seen as 'black boxes' due to their lack of interpretability. This situation presents challenges in identifying reasons ...
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...
BACKGROUND: Artificial intelligence (AI)-assisted image interpretation is a fast-developing area of clinical innovation. Most research to date has focused on the performance of AI-assisted algorithms in comparison with that of radiologists rather tha...
Journal of the American College of Radiology : JACR
39566875
OBJECTIVE: To assess whether the implementation of deep learning (DL) computer-aided detection (CAD) that screens for suspected pneumothorax (PTX) on chest radiography (CXR) combined with an electronic notification system (ENS) that simultaneously al...
PURPOSE: Pneumothorax (PTX) is a common clinical urgency, its diagnosis is usually performed on chest radiography (CXR), and it presents a setting where artificial intelligence (AI) methods could find terrain in aiding radiologists in facing increasi...
The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pediatric chest radiographs and to assess its diagnostic performance. Chest radiographs from patients un...
Journal of vascular and interventional radiology : JVIR
39662619
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear w...