AIMC Topic: Radiologists

Clear Filters Showing 211 to 220 of 503 articles

Added value of an artificial intelligence solution for fracture detection in the radiologist's daily trauma emergencies workflow.

Diagnostic and interventional imaging
PURPOSE: The main objective of this study was to compare radiologists' performance without and with artificial intelligence (AI) assistance for the detection of bone fractures from trauma emergencies.

European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

Pediatric radiology
A new task force dedicated to artificial intelligence (AI) with respect to paediatric radiology was created in 2021 at the International Paediatric Radiology (IPR) meeting in Rome, Italy (a joint society meeting by the European Society of Pediatric R...

Combined artificial intelligence and radiologist model for predicting rectal cancer treatment response from magnetic resonance imaging: an external validation study.

Abdominal radiology (New York)
PURPOSE: To evaluate an MRI-based radiomic texture classifier alone and combined with radiologist qualitative assessment in predicting pathological complete response (pCR) using restaging MRI with internal training and external validation.

Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study.

AJR. American journal of roentgenology
Deep learning-based convolutional neural networks have enabled major advances in development of artificial intelligence (AI) software applications. Modern AI applications offer comprehensive multiorgan evaluation. The purpose of this article was to...

Use of artificial intelligence in emergency radiology: An overview of current applications, challenges, and opportunities.

Clinical imaging
The value of artificial intelligence (AI) in healthcare has become evident, especially in the field of medical imaging. The accelerated pace and acuity of care in the Emergency Department (ED) has made it a popular target for artificial intelligence-...

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

European radiology
OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed ...

Artificial Intelligence (AI) for Lung Nodules, From the Special Series on AI Applications.

AJR. American journal of roentgenology
Interest in artificial intelligence (AI) applications for lung nodules continues to grow among radiologists, particularly with the expanding eligibility criteria and clinical utilization of lung cancer screening CT. AI has been heavily investigated f...

The feasibility to use artificial intelligence to aid detecting focal liver lesions in real-time ultrasound: a preliminary study based on videos.

Scientific reports
Despite the wide availability of ultrasound machines for hepatocellular carcinoma surveillance, an inadequate number of expert radiologists performing ultrasounds in remote areas remains a primary barrier for surveillance. We demonstrated feasibility...