projeto
Clustering Heart Disease Patient Data
Iniciante
Updated 06/2024Iniciar Projeto Gratuitamente
Incluído comPremium or Teams
10 Tasks1,500 XP4,194
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Tentar DataCamp for BusinessProject Description
Doctors frequently study former cases to learn how to best treat their patients. A patient who has a similar health history or symptoms to a previous patient could benefit from undergoing the same treatment. This project investigates whether doctors might be able to group together patients to target treatments using common unsupervised learning techniques. In this project you will use k-means and hierarchical clustering algorithms.
The dataset for this project contains characteristics of patients diagnosed with heart disease. It can be found here.
Project Tasks
- 1Targeting treatment for heart disease patients
- 2Quantifying patient differences
- 3Let's start grouping patients
- 4Another round of k-means
- 5Comparing patient clusters
- 6Hierarchical clustering: another clustering approach
- 7Hierarchical clustering round two
- 8Comparing clustering results
- 9Visualizing the cluster contents
- 10Conclusion
Technologies
R
Megan Robertson
Ver MaisData Scientist