Enhancing Healthcare Transparency: Leveraging Machine Learning, GIS Mapping and Power BI for Private Hospital Insurance Claims Analysis

This project focuses on developing a machine learning-driven system to classify hospital claims and treatment outcomes, offering a second opinion on healthcare costs and decision-making for insurance claims and treatment efficacy.

Key Features and Tools:

• Machine Learning Algorithms: Leveraging Python (pandas, numpy, scikit-learn) for predictive modeling to assess claim validity and treatment outcomes.
• APIs Integration: Used Google Maps API to retrieve and map the locations of private hospitals in Malaysia.
• GIS Mapping Dashboard: Created a GIS-enabled dashboard in Microsoft Power BI to visualize private hospital distribution across Malaysia, aiding healthcare planning and analysis.
• Advanced Analytics Tools: Integrated Microsoft Excel, Python, and Google Collab for data processing and automation workflows.