Data Liberation and Crowdsourcing in Medical Research: The Intersection of Collective and Artificial Intelligence.
Radiol Artif Intell
; 6(1): e230006, 2024 Jan.
Article
in En
| MEDLINE
| ID: mdl-38231037
ABSTRACT
In spite of an exponential increase in the volume of medical data produced globally, much of these data are inaccessible to those who might best use them to develop improved health care solutions through the application of advanced analytics such as artificial intelligence. Data liberation and crowdsourcing represent two distinct but interrelated approaches to bridging existing data silos and accelerating the pace of innovation internationally. In this article, we examine these concepts in the context of medical artificial intelligence research, summarizing their potential benefits, identifying potential pitfalls, and ultimately making a case for their expanded use going forward. A practical example of a crowdsourced competition using an international medical imaging dataset is provided. Keywords Artificial Intelligence, Data Liberation, Crowdsourcing © RSNA, 2023.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Biomedical Research
/
Crowdsourcing
/
Holometabola
Limits:
Animals
Language:
En
Journal:
Radiol Artif Intell
Year:
2024
Document type:
Article