Cardiovascular Researcher Roundtable: Using Large-Scale Datasets for Predicting Disease Probability

Advances in large-scale datasets represent an exciting opportunity for insights into various types of diseases. Large-scale datasets present an opportunity to build more robust and less biased models for predicting disease probability. Incorporating these datasets is becoming more common especially as a driver for more in-depth insights into cardiovascular disease.

Watch the panel of expert cardiovascular disease researchers as they discuss the latest advances in their field of study. They discuss their research experience, recent advances and potential roadblocks in furthering our understanding of cardiovascular disease. The panel then dives into incorporating large-scale datasets, and the importance of cloud computing and global scientific collaboration networks.

00:00 Speaker Introductions
02:00 Why Cardiovascular Disease Research?
04:21 Genomic Data & Drug Effects
09:40 Incorporating Various Data Types
11:05 Specific Phenotypes for Cardiovascular Research
13:25 Research Deriving Features from Primary Data
15:36 Machine Learning Methods on Large-Scale Datasets
17:28 Communicating Machine Learning Results to Clinicians
20:05 Cloud Environments & Large-Scale Datasets
23:13 Importance of Research Community & Diversity
27:30 RAP & Cardiovascular Research
30:30 Clinical Institutions, Cloud Computing & UK Biobank
42:08 Handheld Devices, Data & Risk Scores
47:12 Genomics & Cardiology Assessments