Deep learning techniques for imaging diagnosis and treatment of aortic aneurysm.

Objective: This study aims to review the application of deep learning techniques in the imaging diagnosis and treatment of aortic aneurysm (AA), focusing on screening, diagnosis, lesion segmentation, surgical assistance, and prognosis prediction.

Methods: A comprehensive literature review was conducted, analyzing studies that utilized deep learning models such as Convolutional Neural Networks (CNNs) in various aspects of AA management. The review covered applications in screening, segmentation, surgical planning, and prognosis prediction, with a focus on how these models improve diagnosis and treatment outcomes.

Angiotensin-converting enzyme I/D polymorphism and aortic aneurysm risk: a meta-analysis.

Objectives: Angiotensin-converting enzyme (ACE) I/D polymorphism has been implicated in aortic aneurysm risk, but individual published studies show inconclusive results. The aim of this study was to explore a more precise estimation of its relation with aortic aneurysm using meta-analysis.

Methods: Electronic searches of PubMed and EMBASE databases were conducted for all publications through February 2014.