A 'datathon' model to support cross-disciplinary collaboration
| Autor: | Mohammad M. Ghassemi, Louis Mayaud, Tom J. Pollard, Ned McCague, David J. Stone, Kenneth E. Paik, Peter Charlton, Matthieu Resche-Rigon, Tristan Naumann, Mengling Feng, Jerome Aboab, Dominic C Marshall, Justin D. Salciccioli, Leo Anthony Celi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
020205 medical informatics
business.industry Cross disciplinary Perspective (graphical) Statistics as Topic 02 engineering and technology General Medicine Models Theoretical Data science Replication (computing) Article 03 medical and health sciences 0302 clinical medicine Databases as Topic Health care 0202 electrical engineering electronic engineering information engineering Medicine Interdisciplinary communication Interdisciplinary Communication 030212 general & internal medicine Cooperative behavior Cooperative Behavior business |
| Zdroj: | Science Translational Medicine |
| Popis: | In recent years, there has been a growing focus on the unreliability of published biomedical and clinical research. To introduce effective new scientific contributors to the culture of health care, we propose a "datathon" or "hackathon" model in which participants with disparate, but potentially synergistic and complementary, knowledge and skills effectively combine to address questions faced by clinicians. The continuous peer review intrinsically provided by follow-up datathons, which take up prior uncompleted projects, might produce more reliable research, either by providing a different perspective on the study design and methodology or by replication of prior analyses. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|