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KTHAIS x ABC Labs x KTH Longevity- MedAI Hackathon

lumaHosted on Luma

Fetched 2 days ago

Monday, September 22, 2025

to Sunday, September 28, 2025

•

6 days long

Artificial IntelligenceMachine LearningHealthtechSocial Impact

Event Type

in person

12

Participants

1

Est. Projects

🚀 Put your machine learning skills to the test in medtech! Join KTH AI Society, ABC Labs, KTH Innovation, and KTH Longevity for a one-week AI hackathon where you’ll tackle a real-world challenge in drug testing and lab automation The Challenge:Thousands of drug test samples need manual review to ensure nothing is missed. Your mission is to build a machine learning model that confidently identifies negative LC-MS drug testing samples. Accuracy counts — the better your model, the closer you are to victory! 🏆 The Prize:The winning team will share a prize of 10,000 SEK Who Should Apply:Teams of up to 4 participants who are passionate about AI and medtech. Apply before the 16th September! Key Dates: 22 Sep: Kick-off at ABC Labs Office27–28 Sep: Sprint weekend at KTH Innovation2 Oct: Demo Day As always, food and drinks will be provided on all occasions! ​🔥 Spots are limited, Apply now! About ABC Labs: ABC Labs is a technology-native care provider, diagnostics lab, biobank, and research organisation. Creating unified, exponentially improving, public health products. They are innovating at the frontier of diagnostics by combining software, robotics, data science, medical consultation, lab automation, and operational excellence to create end-to-end products that span the entire spectrum of user needs — and become exponentially more efficient over time

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