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Open video data sharing in developmental science and clinical practice
- Source :
- iScience, Vol 26, Iss 4, Pp 106348- (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- Summary: In behavioral research and clinical practice video data has rarely been shared or pooled across sites due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-heavy computer-based approaches are involved. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing an established and video-based diagnostic tool for detecting neurological deficits. We demonstrated for the first time that, for analyzing infant neuromotor functions, pseudonymization by face-blurring video recordings is a viable approach. The redaction did not affect classification accuracy for either human assessors or artificial intelligence methods, suggesting an adequate and easy-to-apply solution for sharing behavioral video data. Our work shall encourage more innovative solutions to share and merge stand-alone video datasets into large data pools to advance science and public health.
- Subjects :
- Pediatrics
Diagnostics
Clinical neuroscience
Science
Subjects
Details
- Language :
- English
- ISSN :
- 25890042
- Volume :
- 26
- Issue :
- 4
- Database :
- Directory of Open Access Journals
- Journal :
- iScience
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1ac9f20db2774ece9d554ad0977ebf2b
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.isci.2023.106348