Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.
Who will be affected?
Readers: No access to all 28 journals. We recommend accessing our articles via PubMed Central
Authors: No access to the submission form or your user account.
Reviewers: No access to your user account. Please download manuscripts you are reviewing for offline reading before Wednesday, July 01, 2020 at 7:00 PM.
Editors: No access to your user account to assign reviewers or make decisions.
Copyeditors: No access to user account. Please download manuscripts you are copyediting before Wednesday, July 01, 2020 at 7:00 PM.
Sharing data with shared benefits: An AI perspective
Mohammad Tajabadi;
Linus Grabenhenrich;
Adele Ribeiro;
Michael Leyer;
Dominik Heider
ABSTRACT
Artificial intelligence (AI) and data sharing go hand in hand. In order to develop powerful AI models for medical and health applications, data needs to be collected and brought together over multiple centers. However, due to various reasons, including data privacy, not all data can be made publicly available or shared with other parties. Federated and swarm learning can help in these scenarios. However, in the private sector, such as between companies, the incentive is limited, as the resulting AI models would be available for all partners irrespective of their individual contribution, including the amount of data provided by each party. Here, we discuss a novel and fairer way to encourage companies to engage in collaborative data analysis and AI modeling, ultimately leading to better diagnostic tools.
Citation
Please cite as:
Tajabadi M, Grabenhenrich L, Ribeiro A, Leyer M, Heider D
Sharing Data With Shared Benefits: Artificial Intelligence Perspective