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Data Challenges in Cardiovascular Research

Monday, 24 September 2018, 8.30am to 6.00pm
Location: McGrath Centre, St Catherines's College, University of Cambridge

Cardiovascular disease is the biggest killer in the world, causing nearly 18 million deaths per year. Healthcare systems around the world are struggling with the increased disease burden caused by lifestyle factors and the aging populations, and new ways are urgently needed to guide disease prevention, to improve disease detection and diagnosis, and to monitor and manage diseases. Common to all of the above focus areas is the large amount of data produced.

Big Data SRI and Cardiovascular SRI have joined forces to raise awareness of the types of data-related challenges in cardiovascular research and to maximise collaborative opportunities between clinical and computational research groups in Cambridge.

This collaboration will be launched on Monday 24th September 2018 at St Catharine's College through a free, full-day research showcase event, and will be followed up in 2019 with a series of smaller workshops supporting collaborations around specific research questions.

We will host a mixture of long (25min) and short (10min) talks with extended breaks between sessions to allow time for discussions.

 

Registration

Registration for this event is now closed.

 

Programmme

Time Session Presentation
08:30 - 09:00 Registration and Refreshments
 

 

   

Session 1 - Chair: TBC

09:00 - 09:10 Welcome Prof Martin Bennett
     
09:10 - 09:50 Keynote: TBC Dr Brian Ference
     
09:50 - 10:15 Landmark models for optimizing the use of repeated measurements of risk factors in electronic health records to predict future disease risk Dr Angela Wood
     
10:15 - 10:30 Combining evidence from multiple data sources within a discrete event simulation for decision modelling: should we screen women for abdominal aortic aneurysm? Dr Michael Sweeting
 

 

 
     
10:30 - 11:00 Morning Tea and Coffee
   
Session 2 - Chair: TBC
11:00 - 11:25 Imaging human cardiac metabolism by ultra-high field (T7) MRI Prof Chris Rodgers
     
11:25 - 11:50 Deep learning-based segmentation of CV images Prof Pietro Lio
     
11:50 - 12:10 Atherosclerosis vulnerability assessment Dr Zhongzhao Teng
     
12:10 - 12:30 Compressed sensing meets motion: towards improving highly undersampled MR image reconstruction Dr Angelica Aviles-Rivero
 

 

 
     
12:30 - 13:30 Lunch
   
Session 3 - Chair: TBC
13:30 - 13:55 Finite element simulations to predict valve durability Dr Marta Serrani
     
13:55 - 14:20 Single-cell genomics analysis of muscle development Dr Hongbo Zhang
     
14:20 - 14:45 Exploring the genetic architecture of complex traits to understand disease risk Dr Dragana Vuckovic
     
14:45 - 15:00 Improving predictive modelling of CV events with unstructured data Mr Joydeep Sarkar
     
15:00 - 15:15 Human mitochondrial DNA variants in cardiometabolic traits Dr Ekaterina Yonova-Doing
     
15:15 - 15:30 Genomics of lipid metabolism and the effect of perturbations of lipid levels on CHD risk Dr Eric Harshfield
     
 

 

 
     
15:30 - 16:00 Afternoon Tea and Coffee
   
Session 4 - Chair: TBC
16:00 - 16:40 Keynote: Machine learning for medicine: Predicting, pre-empting and treating disease Prof Mihaela van der Schaar
     
16:40 - 16:50 Closing Remarks Prof Martin Bennett
     
16:50 - 18:00 Drinks Reception & Networking

 

This event is jointly organised by the Cambridge Big Data Strategic Research Initiativeand Cardiovascular Strategic Research Initiative with support from the Isaac Newton Trust.

Sponsors

Cambridge Big Data
Cambridge Cardiovascular