Medical Real World Problem Statement :-
Cardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated 17.9 million lives each year, which accounts for 31% of all deaths worlwide. Heart failure is a common event caused by CVDs and this dataset contains 12 features that can be used to predict mortality by heart failure.
If you're able to make a machine learning model, then this will help in early detection and people can be saved.
You have to predict a person death event using some features:-
Age ,Gender , blood pressure, smoke, diabetes,ejection fraction, creatinine phosphokinase, serum_creatinine, serum_sodium, time
Dataset link:- https://www.kaggle.com/andrewmvd/heart-failure-clinical-data