A cross-disciplinary collaborative "Datathon" model to promote the application of medical big data
10.3760/cma.j.issn.2095-4352.2018.06.021
- VernacularTitle:推动医疗大数据应用落地的跨学科Datathon模式探索
- Author:
Yuan ZHANG
1
;
Peiyao LI
;
Yuzhuo ZHAO
;
Tongbo LIU
;
Zhengbo ZHANG
;
Desen CAO
;
Tanshi LI
;
Celi Anthony LEO
Author Information
1. 解放军医学院
- Keywords:
Big data in healthcare;
Application of medical big data;
Cross-disciplinary collaboration;
Datathon
- From:
Chinese Critical Care Medicine
2018;30(6):606-608
- CountryChina
- Language:Chinese
-
Abstract:
Medical practice generates and stores immense amounts of clinical process data, while integrating and utilization of these data requires interdisciplinary cooperation together with novel models and methods to further promote applications of medical big data and research of artificial intelligence. A "Datathon" model is a novel event of data analysis and is typically organized as intense, short-duration, competitions in which participants with various knowledge and skills cooperate to address clinical questions based on "real world" data. This article introduces the origin of Datathon, organization of the events and relevant practice. The Datathon approach provides innovative solutions to promote cross-disciplinary collaboration and new methods for conducting research of big data in healthcare. It also offers insight into teaming up multi-expertise experts to investigate relevant clinical questions and further accelerate the application of medical big data.
