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CodeBlue

devpostHosted on Devpost

Fetched 1 day ago

Thursday, June 4, 2026

to Saturday, June 6, 2026

•

3 days long

Data ScienceArtificial IntelligenceHealthtech
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.

Event Type

online

44

Participants

$1,000

Prize Pool

3

Est. Projects

Code Blue is a medical AI hackathon designed to introduce high school students to the intersection of artificial intelligence, bioinformatics, and healthcare. We're hosting this event at a pivotal moment. AI is transforming medicine, and we want to get the next generation involved in building solutions that matter. Over the course of this hackathon, you'll work on real-world challenges in medical AI. Whether you're diagnosing diseases from imaging data, building conversational tools to support patients and physicians, or analysing genomic information to identify health risks, you'll be solving problems that have a genuine impact in the healthcare industry. No prior experience necessary. We'll provide datasets, mentorship, and resources to guide you through each challenge track. Our goal isn't just to build innovative prototypes; it's to spark your curiosity about bioinformatics and show you what's possible when technology meets medicine. By the end of Code Blue, you'll have hands-on experience in one of the fastest-growing fields in tech and hopefully, the inspiration to pursue this further. If you're curious about how AI can solve real healthcare problems, this is your chance to get your hands dirty and build something meaningful.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct