Deep learning of recorded behaviour discriminates visual losses in infants
The analysis of behavioural patterns from standardized video recordings of infants with varying degrees of visual impairment allows, via deep learning, to discriminate the infants by visual-impairment severity and by ophthalmological condition.
Published in Bioengineering & Biotechnology
Like
Be the first to like this
Chief Editor, Nature Biomedical Engineering, Nature Research
Follow the Topic
Biotechnology
Life Sciences > Biological Sciences > Biotechnology
-
Nature Biomedical Engineering
This journal aspires to become the most prominent publishing venue in biomedical engineering by bringing together the most important advances in the discipline, enhancing their visibility, and providing overviews of the state of the art in each field.
Related Collections
With Collections, you can get published faster and increase your visibility.
Implantable wireless communication technologies
This collection brings together research that addresses critical engineering challenges in implantable wireless communications. It demonstrates how electromagnetic, optical, acoustic, or hybrid methods can be engineered to achieve reliable wireless communications and power delivery through biological tissues.
Publishing Model: Hybrid
Deadline: Nov 28, 2026
Biosensing
With this cross-journal Collection, the editors of Communications Biology, Nature Biomedical Engineering, Nature Sensors, Nature Communications, and Scientific Reports welcome the submission of primary research Articles focusing on the development of engineered biosensing devices with the potential to be applied in biomedical research and in the management of disease conditions.
Publishing Model: Hybrid
Deadline: Jun 30, 2026
Please sign in or register for FREE
If you are a registered user on Research Communities by Springer Nature, please sign in
The cover illustrates the deep-learning-based classification of infants by ophthalmic condition via a deep-learning algorithm trained on standardized video recordings of the behaviour of infants with varying degrees of visual impairment.
See Long et al.
Image: Haotian Lin and Yifan Xiang, Zhongshan Ophthalmic Center, Sun Yat-sen University. Cover design: Alex Wing