🔍 Introduction and goal¶

Cancer is the second leading cause of death in Europe. With 3.7 million new cancer cases in Europe each year, it is clear that clinicians require innovative tools and resources to improve cancer diagnosis, therapy, patient selection, and prediction. Artificial intelligence (AI) has emerged as a promising technology that can support these goals. In the search for new AI opportunities to advance medical research and improve patient outcomes, the consortium partners of the EU-funded CHAIMELEON Project have created the CHAIMELEON Open Challenges. 

The CHAIMELEON Project develops an EU-wide interoperable repository that will enable researchers, data scientists, and clinicians to develop and validate AI tools for improved cancer management. It aims to create a cloud-based data repository of cancer images. This repository will have multimodality imaging and related clinical data from patients diagnosed with lung, breast, prostate, and colorectal cancers, making it one of the most comprehensive of its kind in Europe. The project brings together a consortium of 18 organisations across Europe, including research institutions, hospitals, and companies specialising in AI and medical imaging. 

👩‍🔬👨‍🔬 The CHAIMELEON Open Challenges¶

The CHAIMELEON Open Challenges is a competition designed to train and refine AI models to answer clinical questions about five types of cancer: prostate, lung, breast, colon, and rectal. Participants are challenged to collaborate and develop innovative AI-powered solutions that can significantly impact cancer diagnosis, management, and treatment. They will be evaluated considering a balance between the performance of their AI algorithms to predict different clinical endpoints such as disease staging, treatment response or progression free survival and their trustworthiness. 

The challenges are open to the whole scientific and tech community interested in AI. They are a unique opportunity to showcase how AI can be used to advance medical research and improve patient outcomes within the CHAIMELEON project. 

The challenges will be divided in two phases: the Classification Phase and the Championship Phase. 

The Classification Phase has already started and will extend until to January 15th, 2024. In this phase, any participant can join and download a highly controlled cancer dataset. The dataset will consist of post-processed (i.e., harmonised) images associated with specific clinical variables, ensuring a level playing field for all participants. The participants will train their AI models and compete to be among the top on the leaderboard.  

The Championship Phase will extend from January 16th, 2024 to February 29th, 2024. In this phase the top 40 participants from the previous phase will be invited to compete on an even grander stage, using the CHAIMELEON platform to train their algorithms. This phase will include five different challenges, one for each cancer type (prostate, lung, breast, colon, and rectal), with a total prize pool of 20.000€ per challenge, split among the winners. Original images and associated clinical data, along with different image pre-processing and harmonization tools, will be available to participants who have passed the qualifying round cut-off point. The same computational resources will be assigned to each participant; therefore, each participant can decide which challenges to tackle and apply their strategies accordingly.  

🏅 Prizes¶

Those who take on the challenge can win a total prize pool of €20,000 per challenge, split amongst the winners, with €100,000 in prizes. 

This phase will include five different challenges, one for each cancer type (prostate, lung, breast, colon, and rectal), with a total prize pool of 20.000€ per challenge, split among the winners:  

The winners of the Challenges will be awarded with a total prize pool of 20k€ per challenge, split among the winners (allowance of 100k € under Coordinator´s budget) and with the inclusion of their AI-based solutions for Clinical Validation in WP9 thus accelerating their path to market at no cost to them. The participants in the Challenge will need to commit providing ChAImeleon with feedback on their user experience and provide metrics on the performance of their AI-based solutions before and after their experimentation with ChAImeleon. 

👥 Organizers¶

The project brings together a consortium of 18 organisations across Europe, including research institutions, hospitals, and companies specialising in AI and medical imaging:  Fundación para la Investigación del Hospital Universitario la Fe de la Comunidad Valenciana (ES), Universita di Pisa (IT), Universita Degli Studi di Roma la Sapienza (IT), Centro Hospitalar Universitário de Santo António (PT), ICCS Policlinico San Donato (IT), College des Enseignants de Radiologie (FR), Universiteit Masstricht (NL), Charité Universitätsmedizin Berlin (DE), Imperial College London (UK), Ben-Gurion University of the Negev (IL), Universitat Politècnica de Valencia (ES), GE Healthcare (DE), Quibim (ES), Medexprim (FR), Bahia (ES), Matical Innovation (ES), European Institute of Biomedical Imaging Research (AT), Universitat de Valencia (ES). 

The CHAIMELEON project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952172. 

Privacy

The Chaimeleon Open Challenges complies with the strictest data privacy regulations and ethical standards.

Disclaimer 

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.