Background Non-contrast head CT scan is the current standard for initial imaging of patients
with head trauma or stroke symptoms. We aimed to develop and validate a set of deep …

Importance: Non-contrast head CT scan is the current standard for initial imaging of patients
with head trauma or stroke symptoms. Objective: To develop and validate a set of deep …

Computed tomography (CT) of the head is used worldwide to diagnose neurologic
emergencies. However, expertise is required to interpret these scans, and even highly …

Purpose To analyze the implementation of deep learning software for the detection and
worklist prioritization of acute intracranial hemorrhage on non-contrast head CT (NCCT) in …

Purpose To evaluate the performance of an artificial intelligence (AI) tool using a deep
learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non …

Background Highly accurate detection of intracranial hemorrhages (ICH) on head computed
tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to …

Artificial intelligence is a rapidly evolving field, with modern technological advances and the
growth of electronic health data opening new possibilities in diagnostic radiology. In recent …

To investigate the performance of a joint convolutional neural networks-recurrent neural
networks (CNN-RNN) using an attention mechanism in identifying and classifying …

BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology
for image recognition. This study evaluates a convolutional neural network optimized for the …

Objective To determine the institutional diagnostic accuracy of an artificial intelligence (AI)
decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on …