EACTS/STS Guidelines for diagnosing and treating acute and chronic syndromes of the aortic organ

M Czerny, M Grabenwöger, T Berger… - European Journal of …, 2024 - academic.oup.com
These guidelines, endorsed by both the EACTS and STS, represent the official viewpoint on
this topic. They show a commitment to ongoing improvement, as regular updates will be …

An extensive review on deep learning and machine learning intervention in prediction and classification of types of aneurysms

RA Sinnaswamy, N Palanisamy… - Wireless Personal …, 2023 - Springer
Aneurysm (Rupture of blood vessels) may happen in the cerebrum, abdominal aorta and
thoracic aorta of humans, which has a high fatal rate. The advancement of the artificial …

A benchmark study of convolutional neural networks in fully automatic segmentation of aortic root

T Yang, G Zhu, L Cai, JH Yeo, Y Mao… - … in Bioengineering and …, 2023 - frontiersin.org
Recent clinical studies have suggested that introducing 3D patient-specific aortic root
models into the pre-operative assessment procedure of transcatheter aortic valve …

Assessing the accuracy of an artificial intelligence-based Segmentation algorithm for the Thoracic aorta in computed tomography applications

C Artzner, MN Bongers, R Kärgel, S Faby, G Hefferman… - Diagnostics, 2022 - mdpi.com
The aim was to evaluate the accuracy of a prototypical artificial intelligence-based algorithm
for automated segmentation and diameter measurement of the thoracic aorta (TA) using CT …

AI tools in Emergency Radiology reading room: a new era of Radiology

SK Dundamadappa - Emergency Radiology, 2023 - Springer
Artificial intelligence tools in radiology practices have surged, with modules developed to
target specific findings becoming increasingly prevalent and proving valuable in the daily …

A deep convolutional neural network ensemble for composite identification of pulmonary nodules and incidental findings on routine PET/CT

JH Chamberlin, C Smith, UJ Schoepf, S Nance… - Clinical Radiology, 2023 - Elsevier
AIM To evaluate primary and secondary pathologies of interest using an artificial intelligence
(AI) platform, AI-Rad Companion, on low-dose computed tomography (CT) series from …

A Survey of Machine Learning Approaches for Segmentation of Cardiovascular Neurocristopathy related Images

T Iqbal, O Soliman, S Sultan, I Ullah - IEEE Access, 2023 - ieeexplore.ieee.org
Cardiovascular neurocristopathy is associated with abnormal migration and development of
neural crest cells, impacting the neural and the human cardiovascular system and leading to …

Artificial Intelligence Provides Accurate Quantification of Thoracic Aortic Enlargement and Dissection in Chest CT

N Fink, B Yacoub, UJ Schoepf, E Zsarnoczay, D Pinos… - Diagnostics, 2024 - mdpi.com
This study evaluated a deep neural network (DNN) algorithm for automated aortic diameter
quantification and aortic dissection detection in chest computed tomography (CT). A total of …

DeepVox and SAVE-CT: a contrast-and dose-independent 3D deep learning approach for thoracic aorta segmentation and aneurysm prediction using computed …

M del-Valle, LL de Oliveira, HC Vieira, HMH Lee… - arXiv preprint arXiv …, 2023 - arxiv.org
Thoracic aortic aneurysm (TAA) is a fatal disease which potentially leads to dissection or
rupture through progressive enlargement of the aorta. It is usually asymptomatic and …

Deploying clinical machine learning? Consider the following...

C Lu, K Chang, P Singh, S Pomerantz, S Doyle… - arXiv preprint arXiv …, 2021 - arxiv.org
Despite the intense attention and considerable investment into clinical machine learning
research, relatively few applications have been deployed at a large-scale in a real-world …