TY - JOUR
T1 - A “datathon” model to support cross-disciplinary collaboration
AU - Aboab, Jerome
AU - Celi, Leo
AU - Charlton, Peter
AU - Feng, Mengling
AU - Ghassemi, Mohammad
AU - Marshall, Dominic
AU - Mayaud, Louis
AU - Naumann, Tristan
AU - McCague, Ned
AU - Paik, Kenneth
AU - Pollard, Tom
AU - Resche-Rigon, Matthieu
AU - Salciccioli, Justin
AU - Stone, David
PY - 2016/4/6
Y1 - 2016/4/6
N2 - 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.
AB - 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.
U2 - 10.1126/scitranslmed.aad9072
DO - 10.1126/scitranslmed.aad9072
M3 - Article
SN - 1946-6234
VL - 8
SP - 333ps8
JO - Science Translational Medicine
JF - Science Translational Medicine
IS - 333
ER -