Data Science Bowl Winners Harness AI to Accelerate Life-Saving Medical Research

Imagine unleashing the power of artificial intelligence to automate a critical component of biomedical research, expediting life-saving research in the treatment of almost every disease from rare disorders to the common cold. This could soon be a reality, thanks to the fourth Data Science Bowl, a 90-day competition in which, for the very first time, participants trained deep learning models to examine images of cells and identify nuclei, regardless of the experimental setup--and without human intervention. Algorithms developed in this competition could save researchers hundreds of thousands of hours of effort per year. This year, the competition brought together nearly 18,000 global participants, the most ever for the Data Science Bowl. Collectively, they submitted more than 68,000 algorithms and worked an estimated 288,000 hours to automate the vital, but time-consuming, process of nuclei detection.