We aim to develop a predictive model for cerebral stroke using a dataset with multiple variables. Our goal is to create an accurate model that can identify individuals at high risk of stroke, enabling healthcare professionals to intervene early and prevent potential stroke incidents.
Technology
Python, SAS EM , SAS Enterprise Guide
Region
USA
Team lead
Sanjam Patwalia
Team members
Kumar Yash, Anuj Pratap Singh, Raja Bobba
Social media handles
*all team members' social media links here*
Is your team interested in participating in an interview?
Very interesting work on cerebral stroke, Team Spears! I expected to see Age, BMI, Glucose, and Smoking status highly correlated with cerebral stroke. In particular, stroke is highly correlated with age - which tell us to not get old 🙂
If you could supplement your analysis with additional data to further unpack risk factors than individuals can control, what would you choose? I'm simply thinking about additional "calls to action" for individuals seeking to actively work to reduce their risk of stroke.
Good news: We've extended SAS Hackathon registration until Sept. 12, so you still have time to be part of our biggest event yet – our five-year anniversary!
