Welcome to my data analysis portfolio, where I showcase projects focused on healthcare data and health informatics. As healthcare data analyst, I am dedicated to leveraging data for meaningful insights and addressing healthcare challenges. Explore this collection to see how I integrate principles of health informatics to enhance the understanding and application of data-driven solutions.

• 👋 Hi, I'm @winok2, a passionate graduate student with a focus on health informatics.
• 👀 Interested in data analysis, data visualization, machine learning, and their applications in healthcare.
• 🌱 Currently expanding my knowledge of data science techniques and machine learning in the context of health informatics.
• 💞️ Looking to collaborate on open-source healthcare data projects and engaging data analysis challenges.
• 📫 Reach me via email or connect on LinkedIn.
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Description: Utilized Python (Pandas, NumPy, Matplotlib, Seaborn) in analyzing a study data to understand the impact of cash incentives on HIV disclosure. Explores key factors, including age, distance, and incentives.

Repository: link.

Description: The findings highlight a worrisome: escalation in CO2 emissions, persistent growth in urban population, alarming reduction in forest cover, and a concerning downturn in renewable energy consumption. These observations underscore the urgency for sustainable environmental practices and informed policymaking to address the evolving climate challenges in Kenya. Technologies Used: Power BI and its inbuilt M language.

Repository: link

Description: This project holds significant real-world implications as it tackles the challenge of extracting valuable insights from unstructured Electronic Health Record (EHR) clinical notes. By employing Regex and Python, the aim is to enhance the understanding of patient health narratives, enabling more informed healthcare decisions and contributing to the advancement of personalized medicine.

Repository: link

Description: This project is crucial for healthcare intervention planning, utilizing Python (for meticulous data cleaning and joining) and Power BI (for effective visualization). By examining patient data, it offers valuable insights into specific risk categorie, guiding the development of tailored healthcare interventions and preventive measures against the potential development of Coronary Artery Disease (CAD) over the next decade.

Repository: link

This portfolio is open-source and available under the MIT License. Please provide proper attribution when using, modifying, or sharing the code and findings.

Gratitude to the open-source data analyis softwares, plethora of free online data sets and the authors of the libraries and tools that contribute to the success of these projects