Biomedical Engineer transitioning to Data Analyst. @LilianaMA
Skilled in SQL, Python, Power BI and Tableau.
This project involved an extensive analysis and prediction of publicly available hospital discharge data from Aguascalientes, Mexico, sourced from SSA/DGIS. Python was utilized for data cleaning, preparation, exploration, and visualization. Furthermore, a classification model using XGBoost was constructed to predict patient discharge reasons. The project provided valuable insights into hospital discharge patterns and patient outcomes.
This project, inspired by Data Wizardry, explores the analysis and visualization of Real-world Fake Data #RWFD concerning hospital emergency room admissions. Employing Tableau, the project uncovers valuable patterns, trends, and insights within patient visits, including peak admission times, average waiting times, and patient satisfaction.
This project focuses on the application of SQL Server to perform comprehensive data cleaning and preprocessing of the Medical Students synthetic dataset from Kaggle. Additionally, it involves an in-depth statistical analysis and data exploration to uncover relationships between various variables and the presence or absence of diabetes.