Heart diseases, if left undetected, pose a significant threat to global health, leading to severe complications such as stroke, which, according to the World Health Organization, is the 2nd leading cause of death worldwide, contributing to around 11% of total deaths. Particularly in Canada, heart diseases remain a pressing health issue with the Heart and Stroke Foundation reporting one person dying every five minutes due to heart disease, stroke, or related conditions, and being a primary cause of hospitalization.
In this datathon, we leverage the potential of Machine Learning and Exploratory Data Analysis for early prediction and detection of heart diseases using real-world datasets. The main objective of this datathon is to explore the efficacy of utilizing machine learning in the detection of cardiovascular events and understanding the clinical, social, and behavioral factors that might contribute to them. We will be utilizing the datasets provided for this purpose and hope to present a compelling and coherent data analysis story to our stakeholders.