It’s all in the timing: calibrating temporal penalties for biomedical data sharing

By Weiyi Xia, Zhiyu Wan, Zhijun Yin, James Gaupp, Yongtai Liu, E. Clayton, Murat Kantarcioglu, Yevgeniy Vorobeychik, Bradley A. Malin. 2018

12 citations recorded by the source corpus.

Subfields: Genetics, Information Systems, Public Health, Environmental and Occupational Health

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Jayashree Kalpathy-Cramer
2. Daniel L. Rubin
3. Niranjan Balachandar
4. Carson K. Lam
5. Ken Chang
6. Darvin Yi
7. James M. Brown
8. Bruce R. Rosen

Citations in the corpus

• Distributed deep learning networks among institutions for medical imaging (2018, background): “Third, patient data is valuable, so institutions might simply prefer not to share data.(10) In such cases, instead of sharing patient data directly, distributing the trained deep learning model may be a more appealing alternative.”