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 …

Brain computed tomography (CTB) scans are widely used to evaluate intracranial pathology.
The implementation and adoption of CTB has led to clinical improvements. However …

Background Methods to improve stratification of small (≤ 15 mm) lung nodules are needed.
We aimed to develop a radiomics model to assist lung cancer diagnosis. Methods Patients …

This retrospective case-control study evaluated the diagnostic performance of a
commercially available chest radiography deep convolutional neural network (DCNN) in …

Labeling errors can significantly impact the performance of deep learning models used for
screening chest radiographs. The deep learning model for detecting pulmonary nodules is …

The applications of artificial intelligence (AI) in radiology are rapidly advancing with AI
algorithms being used in a wide range of disease pathologies and clinical settings. Acute …

Background Artificial intelligence (AI) has been proven useful for the assessment of tubes
and lines on chest radiographs of general patients. However, validation on intensive care …

Background Labeling error may restrict radiography-based deep learning algorithms in
screening lung cancer using chest radiography. Physicians also need precise location …

Objective: Pneumothorax refers to an abnormal accumulation of air in the pleural cavity. This
condition is significant in terms of health and can provide a life-threatening risk, particularly …

Background Tension pneumothorax following trauma is a life-threatening emergency and
radiological investigation is normally discouraged prior to treatment in traditional trauma …