What is a hackathon?

A hackathon is a method of solving a problem as a team over a short period of time. This specific event was cancer AI-themed and served as a great way to bridge the gap between subject matter experts from different areas. The ultimate goal was to learn and have fun while tackling these challenges.

Hosted By

The event was a partnership between The UF Health Cancer Center AI Working Group and Human-Centered Data Science (HCDS) group. The HCDS group focuses on investigating novel applications that cross the boundaries of Databases, Machine Learning, Bioinformatics, and Spatial-Temporal Data Science. The faculty includes the following:

1. Daisy Wang, PhD
2. Kiley Graim, PhD
3. Christan Grant, PhD
4. Zhe Jiang, PhD.

The student chairs were

1. Nathan Gilman
2. Aashish Dhawan
3. Ray Chen
4. Detravious Jamari Brinkley

SIDE NOTE: HCDS seminars are every other week on Friday at 2 PM in Malachowsky Hall. Reach out to the Current HCDS Chairs

Rules

To ensure fairness and collaboration, the following rules were established:

• Each team must attempt one project.
• Teams must consist of at least two people (no solo projects allowed).
• The use of external data is encouraged, and extending existing models is acceptable.

Projects

Teams could choose from three specific projects designed for different data types and skill levels:

1. Predicting breast cancer histopathology:

• The problem: Develop an AI model that can distinguish between ADH and low-grade DCIS in breast histopathology slide images.
• The data: BRACS data includes 189 breast cancer patients, 547 labeled whole slide images, 4539 labeled regions of interest.
• #students on team: 3

2. Cancer patient diet cookbook:

• The problem: Create a AI model that, when provided with a list of dietary restrictions for a cancer patient, will create a recipe book so they can easily follow their specialized diet. The recipe book should include recipes of different cuisines, different cooking skills, and different food budgets. It should implement a therapeutic diet prescription listing specific calories and grams of each macronutrient in the recipes.
• The data: 2 Kaggle datasets
• #students on team: 6

3. Lung cancer metabolomics:

• The problem: Train an AI model on metabolomics dataset to distinguish lung cancer patients from healthy controls. Which metabolites are biomarkers of lung cancer?
• The data: 2 case studies from the Metabolomics Workbench.
• #students on team: 4

Timeline

• Kickoff: Friday, Oct 24th 2025. Meet and greet, then select project.
• Hackathon: Friday, Oct 24th – Sunday, Oct 26th (by midnight). Work on project.
• Date of Event: Wednesday, Nov 5th. A day packed with excitement outlined below
  • Coffee connections AI working group leaders, welcome and opening remarks, keynote speakers, lightning talks, lunch & networking / poster session, hacking cancer with (HCDS), awards ceremony & closing remarks. See details in ad.

Final Thoughts

An enjoyable experience that we plan to host yearly, so sign up for the coming years.

I wrote this in accordance with the slide deck, ad, and my experience.