Robotics & Machine Learning Daily News2024,Issue(Oct.2) :46-46.

Department of Vascular and Endovascular Surgery Reports Findings in Artificial I ntelligence (Digital twin and artificial intelligence technologies for predictiv e planning of endovascular procedures)

Robotics & Machine Learning Daily News2024,Issue(Oct.2) :46-46.

Department of Vascular and Endovascular Surgery Reports Findings in Artificial I ntelligence (Digital twin and artificial intelligence technologies for predictiv e planning of endovascular procedures)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating in Marseil les, France, by NewsRx journalists, research stated, “Current planning of aortic and peripheral endovascular procedures is based largely on manual measurements performed from the 3-dimensional reconstruction of preoperative computed tomogra phy scans. Assessment of device behavior inside patient anatomy is often difficu lt, and available tools, such as 3-dimensional-printed models, have several limi tations.” The news reporters obtained a quote from the research from the Department of Vas cular and Endovascular Surgery, “Digital twin (DT) technology has been used succ essfully in automotive and aerospace industries and applied recently to endovasc ular aortic aneurysm repair. Artificial intelligence allows the treatment of lar ge amounts of data, and its use in medicine is increasing rapidly. The aim of th is review was to present the current status of DTs combined with artificial inte lligence for planning endovascular procedures. Patient-specific DTs of the aorta are generated from preoperative computed tomography and integrate aorta mechani cal properties using finite element analysis. The same methodology is used to ge nerate 3-dimensional models of aortic stent-grafts and simulate their deployment . Post processing of DT models is then performed to generate multiple parameters related to stent-graft oversizing and apposition. Machine learning algorithms a llow parameters to be computed into a synthetic index to predict Type 1A endolea k risk. Other planning and sizing applications include custom-made fenestrated a nd branched stent-grafts for complex aneurysms. DT technology is also being inve stigated for planning peripheral endovascular procedures, such as carotid artery stenting. DT provides detailed information on endovascular device behavior.”

Key words

Marseilles/France/Europe/Angiology/A rtificial Intelligence/Cyborgs/Emerging Technologies/Health and Medicine/Mac hine Learning/Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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