Recently, the global artificial intelligence breast cancer molybdenum target challenge hosted by the Society of Radiology (SPR) in Sao Paulo, Brazil, successfully concluded. The BIG&AI4ONCO team, led by Professor Tao Tan from our school, performed outstandingly in the competition, standing out from 41 participating teams and winning the championship with a high score of 0.838.
Breast cancer is a major disease that seriously threatens women's health worldwide. Early screening and accurate diagnosis play a vital role in improving the survival rate and quality of life of patients. As a routine means of breast cancer screening, the accuracy of molybdenum target examination results is directly related to subsequent diagnosis and treatment decisions. However, accurately predicting the recall situation in molybdenum target inspection has always been a difficult problem that urgently needs to be overcome in the medical field.
In order to promote the in-depth application of artificial intelligence in molybdenum target analysis and improve the efficiency and accuracy of breast cancer screening, SPR, together with several authoritative institutions, generously donated thousands of precious molybdenum target images, built a platform for display and communication for medical professionals and data scientists around the world, and launched this high-profile global AI challenge. This event attracted 41 top teams from all over the world to actively participate in, aiming to optimize the analysis and interpretation of molybdenum target images by developing advanced artificial intelligence algorithms, and provide more effective technical support for early detection of breast cancer. The Kaggle link for this artificial intelligence challenge is https://www.kaggle.com/competitions/spr-screening-mammography-recall/overview.
For the BIG&AI4ONCO team, winning the championship is just a new starting point. The team stated that they will continue to conduct in-depth research on the application of artificial intelligence in the medical field, continuously optimize and improve existing models, and enhance their applicability and reliability in practical clinical environments. At the same time, the team also hopes to cooperate with more medical institutions and scientific research teams to translate the research results into practical clinical applications and provide more accurate and efficient diagnosis and treatment services for more breast cancer patients.
The BIG&AI4ONCO team, led by Professor Tao Tan from our school, won the championship this time, demonstrating the team's strong strength in the intersection of artificial intelligence and medicine, and providing valuable examples for the application of artificial intelligence in the medical field.