We won the SNMMI AI 2024 challenge!
The Society of Nuclear Medicine and Molecular Imaging (SNMMI) AI Task Force, in collaboration with the Physics, Instrumentation, and Data Science Council, announced the commencement of an innovative Radiomics and Machine Learning (ML) Challenge. This competition invited participants to engage with a fully anonymized dataset, which included radiomics features alongside outcome or survival data. Participants were encouraged to utilize this dataset to develop and train ML models to predict patient survival rates. In a subsequent phase of the challenge, these models underwent external validation using a separate dataset containing blinded survival information. The performance of each model was meticulously assessed by the AI challenge team.
This challenge represented a unique opportunity for individuals in the field of radiomics and machine learning to showcase their skills, contribute to the advancement of medical imaging, and potentially impact patient outcomes through innovative predictive modeling.
As we usher in the Persian New Year and the festive spirit of Nowruz, we have more than just the season to celebrate.
In the true spirit of the adage, “A good beginning makes a good ending,” we are elated to announce a remarkable start to the year with our team’s outstanding achievement. We, as the NAIRG team, have emerged as #1 in continuous prediction and #2 in binary classification winners in the prestigious SNMMI AI Challenge, a testament to our collective effort and dedication. Congratulation to all
My colleagues in this challenge
- Arman Gorji, NAIRG
- Amirali Abootorabi, NAIRG
- Nima Sanati, NAIRG
- Dr Mohmamadreza Salmanpour PhD, The University of British Columbia (UBC)
- Prof Arman Rahmim PhD, The University of British Columbia (UBC)
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We do not grow absolutely, chronologically. We grow sometimes in one dimension, and not in another, unevenly. We grow partially. We are relative. We are mature in one realm, childish in another. —Anais Nin
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