BACKGROUND
WHY THIS HACKATHON?
The application of AI and Data Science in the medical field plays a crucial role, especially in analyzing data to help predict the risk of heart disease.
This project provides students with the opportunity to apply Deep Learning techniques to ECG data in order to predict the Coronary Artery Calcium Score — an important indicator of coronary artery blockage.
// LEAD II · REAL-TIME SIMULATION
72
HR bpm
--
CAC SCORE
ECG
INPUT
WORKSHOP & KICKOFF
APR 10, 2026
Room IT204, MUICT
HACKATHON
APR 17–18, 2026
Bit & Byte Room, MUICT
TEAM SIZE
2–4 PEOPLE
Cross-year teams welcome
TARGET
MUICT STUDENTS
All years · All tracks
WHAT YOU'LL GAIN
OBJECTIVES
01
Gain real experience by participating in a university-level Hackathon
02
Apply AI & Data Science to real-world medical problems (Coronary Artery Disease prediction)
03
Develop skills in programming, Deep Learning as well as Soft Skills: communication, teamwork, and time management
SCHEDULE
TIMELINE
10 APRIL 2026
WORKSHOP & KICKOFF
Room IT204 · Faculty of ICT, Mahidol University
Introduction to ECG + Deep Learning + competition briefing
Introduction to ECG + Deep Learning + competition briefing
10 – 16 APRIL 2026
DEVELOPMENT PHASE
Teams develop AI models for Artery Calcium Scoring
17 – 18 APRIL 2026
HACKATHON & PRESENTATION
Meeting Room Bit & Byte · Faculty of ICT, Mahidol University
Develop, finalize, and present projects to judges
Develop, finalize, and present projects to judges
REWARDS
PRIZES
🥇
1ST PLACE
TBA
Winner's prize + certificate + special recognition
🥈
2ND PLACE
TBA
Runner-up prize + certificate
🥉
3RD PLACE
TBA
3rd place prize + certificate
PRIZE DETAILS WILL BE ANNOUNCED SOON — STAY TUNED
QUESTIONS & ANSWERS
FAQ
Who can participate in the ACSE Hackathon 2026?
All currently enrolled students at the Faculty of ICT, Mahidol University are eligible to join — regardless of year (1st–4th) or track. No prior hackathon experience required!
What is the team size?
Teams consist of 2–4 members. Cross-year teams are strongly encouraged. Solo registration is also allowed, and we can help match you with other participants if needed.
What data and tools will be provided?
The dataset (ECG signals with CAC labels) will be provided at the Kickoff on April 10. You can use any open-source tools, libraries, or frameworks — Python, TensorFlow, PyTorch, scikit-learn, etc. Compute resources information will be shared during the kickoff briefing.
Do I need prior AI or Deep Learning experience?
Not required! We will run a workshop on April 10 covering ECG basics and Deep Learning fundamentals. Beginners are very welcome. However, some familiarity with Python will be helpful.
How will teams be judged?
Judging criteria include: (1) Model performance (accuracy/metric score on the test set), (2) Code quality and approach, (3) Presentation clarity and understanding, (4) Innovation in methodology. Full rubric will be provided at kickoff.
What should I bring on hackathon day (Apr 17–18)?
Bring your laptop, charger, and any notes or code you've prepared during the development phase. Food and drinks will be provided. Presentation slides (or notebook) should be ready before the judging session starts.
Can I start coding before the hackathon day?
Yes — the development phase runs April 10–16 after the kickoff. Teams are expected to explore the dataset and build initial models during this period. The hackathon days (Apr 17–18) are for finalizing, improving, and presenting your work.
Is there a registration fee?
No registration fee. The ACSE Hackathon 2026 is completely free for all MUICT students.