The objective of this project is to analyze healthcare datasets to predict disease risk using data analytics and machine learning. The system assists medical professionals by identifying high-risk patients and improving preventive healthcare planning.
Collect healthcare datasets related to patient history and medical parameters.
Perform data cleaning and normalization.
Conduct exploratory data analysis to identify risk factors.
Select relevant features affecting disease occurrence.
Implement classification algorithms such as logistic regression or decision trees.
Train and test predictive models.
Evaluate model performance using accuracy and recall metrics.
Visualize health risk patterns using graphs.
Interpret analytical results for healthcare insights.
Document methodology, results, and ethical considerations.
