How to organise a datathon for bridging between data science and healthcare? Insights from the Technion-Rambam machine learning in healthcare datathon event.

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES

BMJ Health & Care Informatics Pub Date : 2023-09-01 DOI:10.1136/bmjhci-2023-100736

Jonathan Sobel, Ronit Almog, Leo Celi, Michal Yablowitz, Danny Eytan, Joachim Behar

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Abstract

© Author(s) (or their employer(s)) 2023. Reuse permitted under CC BYNC. No commercial reuse. See rights and permissions. Published by BMJ. INTRODUCTION A datathon is a timeconstrained informationbased competition involving data science applied to one or more challenges. Datathons and hackathons differ in their focus, with datathons prioritising data analysis and modelling, while hackathons concentrate on building prototypes. Furthermore, hackathons can encompass a broad range of topics, spanning from software development to hardware design, whereas datathons are more narrowly focused on data analysis. Inperson datathons offer the unique opportunity to learn alongside a community of fellow students and researchers, as well as to directly interact with clinicians and medical professionals. This is in contrast to Kaggle like competitions, which are often selflearning experiences.

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