Natalia Galán-López

I am intrigued by the possibility of collaborating on efficient screening methods for this large-scale systematic review in sports science. Crowdsourcing and machine learning can offer powerful synergies for evidence synthesis.

Some promising approaches could involve using active learning to prioritize documents needing screening. This minimizes expert time on irrelevant studies. We could also apply text classification models to suggest possible includes/excludes, with human verification.

Furthermore, distributing screening tasks across a group of sports science students/fellows via crowdsourcing platforms can accelerate the process. Automated quality control checks can help ensure accuracy.

I believe combining crowdfunding, ML-guided review workflows, and thoughtful design of the human-computer interaction can profoundly enhance systematic reviews. It would be an honor to explore these techniques further and provide methodological support for this important effort to promote women's health in sports.

Please feel free to reach out to me here or via the linked tweet. I look forward to discussing potential collaboration avenues. Together we can advance research synthesis practices and make sports science more inclusive.

Wishing you the best,

#SystematicReview #MachineLearning #SportsScience