Global Medical AI Competition with a USD 9,000 First Prize
Applicant criteria
- No specific age required
- Both
Opportunity criteria
Opportunity description
The Radiological Society of North America (RSNA), in collaboration with Kaggle, is offering the RSNA Knee Abnormality Detection 2026 competition. The competition aims to develop machine learning models capable of detecting a range of important medical conditions in knee MRI scans.
Participants are required to build a multimodal machine learning model that uses medical images together with original radiology reports to detect 12 types of abnormalities and injuries, including ligament tears, meniscal injuries, osteoarthritis, fractures, inflammation, and joint effusion.
Benefits
The total prize pool is USD 77,000.
Main leaderboard prizes include:
First Place: USD 9,000
Second Place: USD 7,000
Third Place: USD 6,500
Fourth Place: USD 6,000
Fifth Place: USD 5,500
Sixth through Tenth Place: USD 5,000 each
A separate Efficiency Track is also available, with the following prizes:
First Place: USD 7,000
Second Place: USD 6,000
Third Place: USD 5,000
Eligibility criteria
The competition is open to individuals and teams through the Kaggle platform.
Participants from countries around the world may enter, subject to any legal or regulatory restrictions imposed by Kaggle or the competition organizer based on the participant’s country of residence.
Applicants must have a Kaggle account and accept the official competition rules before the specified deadline.
Participants may compete individually or form a team in accordance with the rules governing team size and team-merger deadlines.
Participants must use the competition data in accordance with the specified terms of use and licensing conditions.
Submitted entries and models must be created by the participant or team and comply with the competition rules regarding code sharing and external data.
Any external datasets, models, or resources used must be permitted and available for use under the competition rules.
Submissions must be made through Kaggle Notebooks and comply with the competition’s technical requirements.
A medical background is not required. The competition is suitable for participants with experience in artificial intelligence, machine learning, deep learning, computer vision, data science, or medical imaging.