How Data Science Competitions Accelerate Brain Health Discovery

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Abstract

Modern brain health research requires collaboration across multiple disciplines and analytic expertise often lies in the broader scientific community. The inherently heterogeneous nature of brain health data poses significant challenges for both analysis and interpretation, highlighting the importance of interdisciplinary input. Data science competitions provide opportunities to crowdsource solutions for brain data research and clinical application development, by recruiting diverse talent and encouraging collaborative innovation. These competitions provide an open and accessible environment to explore data heterogeneity, benchmark analytic strategies, and translate findings into real-world impact. Here we describe challenges faced by organizers of data science competitions and discuss how they can leverage these competitions — and the diverse expertise they attract — to promote inclusive research, explore data heterogeneity, assess modelling challenges, and translate outcomes into practice.

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