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We analyzed how different demographics of people were correlated with uninsurance rates. We found that Native American and Hispanic populations have higher uninsurance rates.
Identifying Impactful Metrics in Quality Health Plan-Eligible Uninsured Adults
This is my first hackathon project. It is very basic and just pulls and interprets some data from the finance datasets. It doesn't do any statistical analysis, because my only experience is Stor120.
We found that while SVI indicates communities that are less capable of recovering from a catastrophe, it does not highlight which areas are vulnerable to particular natural disasters specific to them.
Forgotten America - How a Conflation of Social, Economic, and Health Challenges are Crippling Eastern Kentucky
Investigating the purchase behavior of app store users and making recommendations for app developers.
Looking at app data, how can we predict the types of apps people use?
Analysis Visualization for IOS Apps
#app#media
Quick report of key demographics of uninsured individuals in Wake County, NC
In our project, we made analyses on the correlations among variables, themes, and hold suggestions towards the government based on our primary interest in the minority in NC.
In the age of rising healthcare and insurance costs, it's absolutely invaluable to identify more efficient solutions for this. Dr. Midas provides an fresh perspective to this problem. Find out how.
Explore the relationship between percent uninsured and other factors
By analyzing demographic data in the Healthcare dataset per NC county, the NC FQHC OI is able to identify opportunities for Federally Qualified Health Centers to expand and improve areas they serve.
How did counties with high Social Vulnerability Indexes fare during the COVID-19 pandemic compared to less vulnerable counties? Did these counties receive enough federal aid?
In our project, we analyze the dataset of the uninsured population by the state and conduct linear regression analysis to better understand the current situation and its related factors.
A webapp to visualize the cost of War and Terrorsim that is supported with a sentiment analyser, that allows a user to map the sentiment of any geographical location using Twitter real time data.
With healthcare dataset and external data, we deployed a practical tool to visualize and predict the disease counts. Using this tool on a county-level, effective policy decisions can be made.
Make the society better
A webapp that visualizes the uninsured rate on a county level. Users can see a map of the uninsured rate for each county, and can click on any given county to show information about that county.
Insight Into New York's Uninsured Population
Using the Social Vulnerability Index (SVI) from the CDC, we've created an interactive dashboard that shows how NC tracts have become more and less vulnerable to social disasters from year-to-year.
We do not simply visualize data. We do real things with data! We want to minimize the unbearable cost natural disasters imposed on human beings by calculating the optimized emergency shelter location.
This analysis aims to observe which features are most helpful in predicting malignant or benign cancer and to see general trends that may aid us in model selection and hyper parameter selection.
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