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

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