We are looking for a PhD-student who will help in an exciting European project. In the VASCUL-AID
project we want to develop an algorithm with AI to predict cardiovascular risks and disease progression in patients with abdominal aortic aneurysms
) and/or peripheral arterial diseases
For both vascular diseases, aortic abdominal aneurysms (AAA) and peripheral arterial diseases (PAD), there is no effective medical therapy. The best current management of these diseases consists of aggressive modification of general cardiovascular risk factors such as targeting cholesterol, blood pressure, and diabetes, next to lifestyle adjustment. A major challenge in current disease management is that to date, it is unclear how progression of vascular diseases and the risk of cardiovascular events are influenced by these risk factors. We cannot predict whose symptoms in PAD patients progress from claudication to rest pain/gangrene. In AAA we cannot predict whose AAA will grow or rupture. There are no means for personalized cardiovascular risk prevention or prediction of cardiocerebrovascular events.The aim of this project VASCUL-AID is:
- To predict the risk of cardiovascular events and progression of the vascular diseases AAA and PAD to influence the course of disease improving the patient's quality of life and care and assisting clinicians to make better-informed decisions involving the patient;
- We will collect data from existing databases, retrospectively from 6 clinical hospitals in Europe and UK. Validation will be done in prospective patient studies in these 6 clinical hospitals as well;
- To this end, we will deliver a clinically relevant and cost-effective trustworthy AI-driven platform (VASCUL-AID) that integrates multi-source parameters including imaging, proteomic and genomic data as well as life-style patient data from wearables to enable personalized vascular disease management.
But to determine which outcome sets needs to be identified as input data and what is seen as relevant data, we are looking for a PhD-student who can help in identifying key outcome sets with the Delphi-method.
For more information, visit: Amsterdam UMC leads an AI-powered hunt for high-risk vascular patientsYour tasks will be:
- Your main task will be to perform literature studies to identify key outcomes for AAA and PAD patients;
- To perform the Delphi methodology based on questionnaires sent to panel of experts and talking to patients;
- Performing cost-effectiveness studies;
- You will closely work together with other PhD candidates (with technical and medical backgrounds);
- You will perform novel academic research combining existing datasets, developing new datasets and identifying datasets relevant for AI;
- You will regularly be presenting the work at (international) conferences, and you will assist in relevant teaching activities;
- You will collaborate with your fellow PhD students and help your fellow clinical PhD students in their trials.