Use of Artificial Intelligence With Deep Learning Approaches for the Follow-up of Infrarenal Endovascular Aortic Repair.
Quentin CoatsaliouFabien LareyreJuliette RaffortClaire WebsterColin D BicknellAnna PounceyEric DucasseCaroline CaraduPublished in: Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists (2024)
The integration of PRAEVAorta AI software into clinical practice promises a transformative shift in post-EVAR surveillance. By offering precise and rapid detection of endoleaks and comprehensive anatomic assessments, clinicians can expect enhanced diagnostic accuracy and streamlined patient management. This innovation reduces reliance on manual measurements, potentially reducing interpretation errors and shortening evaluation times. Ultimately, PRAEVAorta's capabilities hold the potential to optimize patient care, leading to more timely interventions and improved outcomes in endovascular aortic repair.
Keyphrases
- artificial intelligence
- deep learning
- clinical practice
- big data
- machine learning
- convolutional neural network
- public health
- case report
- palliative care
- patient safety
- adverse drug
- abdominal aortic aneurysm
- type diabetes
- emergency department
- risk assessment
- metabolic syndrome
- data analysis
- quality improvement
- insulin resistance
- weight loss
- drug induced
- clinical evaluation