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Imbalanced text classification: lessons learned from tackling the problem of automation of screening in systematic reviews

Counterintuitively, lacking data in the era of big data is a common problem. We will share our story in approaching the challenge of imbalanced classification for the evidence synthesis. You will have an opportunity to find out about the real-life applications from research papers, tips & tricks from the ML practitioner, and also how we contributed to WHO guidelines for keeping distance and wearing masks during the COVID-19 pandemic.

Mateusz Pieniak has been a graduated in Computer Science at the Warsaw University of Technology since 2017. During his studies he started working as a Data Scientist for various companies in different industries. Currently, he works as a Senior Applied NLP Scientist at Evidence Prime, where he creates AI models dedicated to working on better understanding of scientific literature.

Mateusz Pieniak,
Evidence Prime Representative

Monday, 27 September 2021, 2:00-3:30 PM (CEST)

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