Identifying Biomarkers of Cardiovascular Diseases with Machine Learning

Explore a 20-minute talk on identifying biomarkers of cardiovascular diseases using machine learning, presented by Vasileios Nikolaou from Vertex at the Data Science Festival. Delve into the critical challenge of predicting cardiovascular diseases from standardized assessments to develop targeted intervention strategies. Learn about a study using data from the UK household longitudinal study 'Understanding Society' to train machine learning models for identifying biomarkers and risk factors that predict cardiovascular diseases at a ten-year follow-up. Discover how a Gaussian naïve Bayes classifier outperformed logistic regression in recall, enabling the identification of prominent biomarkers. Gain insights into the potential of machine learning for uncovering previously overlooked biomarkers associated with cardiovascular disease onset and its implications for early diagnosis and prevention in future research and practice. Suitable for technical practitioners, this talk was part of the Data Science Festival MayDay event 2024.