[HTML][HTML] Interventional Radiology ex-machina: Impact of Artificial Intelligence on practice

M Gurgitano, SA Angileri, GM Rodà, A Liguori… - La radiologia …, 2021 - Springer
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 …

Myths and facts about artificial intelligence: why machine-and deep-learning will not replace interventional radiologists

F Pesapane, P Tantrige, F Patella, P Biondetti… - Medical Oncology, 2020 - Springer
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 …

[HTML][HTML] Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional …

S Candemir, RD White, M Demirer, V Gupta… - … Medical Imaging and …, 2020 - Elsevier
We propose a fully automated algorithm based on a deep learning framework enabling
screening of a coronary computed tomography angiography (CCTA) examination for …

[HTML][HTML] Optimizing primary healthcare in Hong Kong: strategies for the successful integration of radiology services

CLJ Chow, JS Shum, KTP Hui, AFC Lin, ECP Chu - Cureus, 2023 - ncbi.nlm.nih.gov
The primary healthcare system in Hong Kong plays a crucial role in addressing the
healthcare needs of its population. However, the integration of radiology services into …

[HTML][HTML] Report of the Medical Image De-Identification (MIDI) Task Group-Best Practices and Recommendations

DA Clunie, A Flanders, A Taylor, B Erickson, B Bialecki… - Arxiv, 2023 - ncbi.nlm.nih.gov
1.4 Support This project has been funded in whole or in part with Federal funds from the
National Cancer Institute, National Institutes of Health, under Contract No …

Artificial intelligence in radiology: summary of the AUR academic radiology and industry leaders roundtable

S Chan, J Bailey, PR Ros - Academic radiology, 2020 - Elsevier
The AUR Academic Radiology and Industry Leaders Roundtable was organized as an open
discussion between academic leaders of top US academic radiology departments and …

[HTML][HTML] Temporal Relationship-Aware Treadmill Exercise Test Analysis Network for Coronary Artery Disease Diagnosis

J Wei, B Pan, Y Gan, X Li, D Liu, B Sang, X Gao - Sensors, 2024 - mdpi.com
The treadmill exercise test (TET) serves as a non-invasive method for the diagnosis of
coronary artery disease (CAD). Despite its widespread use, TET reports are susceptible to …

The role of an artificial intelligence ecosystem in radiology

B Allen, R Gish, K Dreyer - Artificial intelligence in medical imaging …, 2019 - Springer
Moving artificial intelligence tools for diagnostic imaging into routine clinical practice will
require cooperation and collaboration between developers, physicians, regulators, and …

Barriers to artificial intelligence adoption in healthcare management: A systematic review

MM Assadullah - Available at SSRN 3530598, 2019 - papers.ssrn.com
Purpose: Humanity has been able to claim the supremacy over other creations through the
intelligence it has been granted. Mimicking this intelligence by computers is artificial …

Enterprise Imaging: The Next Frontier in Healthcare Technology–A Liturature Review

A Liao, E Seeram - Radiology, 2019 - research.monash.edu
Aim A review of the literature was performed to evaluate, review and discuss the imaging
systems of picture archiving and communication system (PACS), vendor neutral archive …