Towards a better understanding of cardio and cerebrovascular diseases
Lead Research Organisation:
University College London
Department Name: Medical Physics and Biomedical Eng
Abstract
Research Potential Impact:
To identify biological and social factors that affect lifelong health, ageing and the development of chronic disease, and to use findings to design and test interventions that enhance healthy ageing
Research Aims:
1. Discover novel features in medical imaging (e.g. echocardiography, magnetic resonance) to predict major clinical outcomes (e.g. heart attack, hospital admission, death).
2. Use novel remote monitoring techniques (e.g. wearable devices and mobile Health devices) to identify trends significantly impacting on long-term cardiovascular health.
3. Develop new predictive models of cerebrovascular disease evolution based on brain MRI imaging and clinical data.
4. Improve the understanding of the possible links between cerebrovascular lesions and cognition.
Research Methodology:
Project will involve applying data science and machine learning techniques to physiological and imaging data to gain better insight into normal ageing and the disease process, with the overarching aim of improving prevention of cardio- and Cerebro-vascular disease and cognitive decline and promoting healthy ageing.
Studentship is available in a partnership between the MRC Unit for Lifelong Health and Ageing, and the Centre for Medical Image Computing. Funding jointly from the MRC LHA, i4health CDT and the BHF accelerator award
To identify biological and social factors that affect lifelong health, ageing and the development of chronic disease, and to use findings to design and test interventions that enhance healthy ageing
Research Aims:
1. Discover novel features in medical imaging (e.g. echocardiography, magnetic resonance) to predict major clinical outcomes (e.g. heart attack, hospital admission, death).
2. Use novel remote monitoring techniques (e.g. wearable devices and mobile Health devices) to identify trends significantly impacting on long-term cardiovascular health.
3. Develop new predictive models of cerebrovascular disease evolution based on brain MRI imaging and clinical data.
4. Improve the understanding of the possible links between cerebrovascular lesions and cognition.
Research Methodology:
Project will involve applying data science and machine learning techniques to physiological and imaging data to gain better insight into normal ageing and the disease process, with the overarching aim of improving prevention of cardio- and Cerebro-vascular disease and cognitive decline and promoting healthy ageing.
Studentship is available in a partnership between the MRC Unit for Lifelong Health and Ageing, and the Centre for Medical Image Computing. Funding jointly from the MRC LHA, i4health CDT and the BHF accelerator award
Organisations
People |
ORCID iD |
| Wenxiao He (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/S021930/1 | 01/10/2019 | 31/03/2028 | |||
| 2872635 | Studentship | EP/S021930/1 | 01/10/2023 | 30/09/2027 | Wenxiao He |