The radiologists were traditionally working in the background. What upgraded them as physicians during the second half of the past century was their clinical training and function precipitated by the evolution of Interventional Radiology and Medical ...
Artificial intelligence in medicine can help improve the accuracy and efficiency of diagnostics, selection of therapies and prediction of outcomes. Machine learning describes a subset of artificial intelligence that utilizes algorithms that can learn...
Journal of vascular and interventional radiology : JVIR
Sep 1, 2022
Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in ima...
Cardiovascular and interventional radiology
Mar 1, 2022
Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this...
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic. AI was mainly introduced via artificial neural network...
The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive CO...
Medical oncology (Northwood, London, England)
Apr 3, 2020
Artificial intelligence (AI) is revolutionizing healthcare and transforming the clinical practice of physicians across the world. Radiology has a strong affinity for machine learning and is at the forefront of the paradigm shift, as machines compete ...
International journal of computer assisted radiology and surgery
Nov 1, 2019
OBJECTIVE: Currently, there is a worldwide shift toward competency-based medical education. This necessitates the use of automated skills assessment methods during self-guided interventions training. Making assessment methods that are transparent and...
AJR. American journal of roentgenology
Oct 1, 2019
The purpose of this article is to describe key potential areas of application of machine learning in interventional radiology. Machine learning, although in the early stages of development within the field of interventional radiology, has great pot...
Since 2012, we have been developing a remote-controlled robotic system (Zerobot®) for needle insertion during computed tomography (CT)-guided interventional procedures, such as ablation, biopsy, and drainage. The system was designed via a collaborati...