Project Story
Inspiration
As INSY students at the University of Texas at Arlington with a newfound interest in data and computing, we embraced the challenge to learn new technologies. Inspired by the pre-event lectures, we started as a team of four. Despite the unexpected departure of our data analysis expert teammates, we persevered through a grueling 24-hour event to gain hands-on experience.
What it does
Our project analyzes a urinalysis dataset provided by Kristian Roger M. Agdeppa, collected from a local clinic in Northern Mindanao, Philippines (April 2020 - January 2023).[link](https://www.kaggle.com/datasets/avarice02/urinalysis-test-results?resource=download)
Our goal was to explore potential correlations between urinalysis results and positive diabetes diagnoses by using graphs we knew how to build.
How we built it
We experimented with MatLab, Taipy, and Pandas, ultimately settling on Pandas for data organization. Gemini's guidance was invaluable in helping us navigate this process.
Challenges we ran into
Our limited experience posed the initial challenge of defining our project focus. After overcoming this, we rapidly learned new software while also managing the departure of key team members. Working through frustrations and troubleshooting issues with Pandas, especially when plotting object-type data, became a significant learning experience.
Accomplishments that we're proud of
We proudly completed our project in 24 hours despite our beginner status. Our resilience in learning, adapting, and challenging ourselves, even without matching the expertise of other teams, is our greatest accomplishment.
What we learned
We gained valuable skills in Pandas, Taipy, and the importance of teamwork. Additionally, networking with participants enriched our understanding of the internet and computing history.
What's next for Correlation of Urinalysis and Positive Diabetes Diagnosis?
We envision sharing our findings with medical professionals and exploring further analysis of this dataset to potentially answer additional research questions around diabetes.
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