Aneurysm detection and growth monitoring through non-invasive peripheral measurements.

该项目涉及脉搏波血液动力学模型的开发，其数值解和相关的波动理论，通过使用非侵入性外周测量开发动脉瘤检测的新方法。然后，这些基于物理的模型将通过机器学习技术进行增强，以提高准确性和鲁棒性。最后，将开发从频繁的半连续外周测量中推断/监测动脉瘤生长的方法，以便预测模型可以在动脉瘤破裂之前告知干预的时间。

This project involves the development of pulse wave haemodynamics models, their numerical solution, and associated wave theory, to develop novel methods for aneurysm detection by using non-invasive peripheral measurements. These physics-based models will then be augmented by machine-learning techniques to increase both accuracy and robustness. Finally, methods to infer/monitor aneurysm growth from frequent semi-continuous peripheral measurements will be developed so that the predictive models can inform on the timing of an intervention prior to aneurysm rupture.