Springer Nature Editor
From the Editors

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.
Go to the profile of Pep Pàmies
Pep Pàmies
Chief Editor, Nature Biomedical Engineering, Nature Research

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

Share with...

...or copy the link

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Preview

Open

Explore the Research

Nature
Nature Nature

Discrimination of the behavioural dynamics of visually impaired infants via deep learning - Nature Biomedical Engineering

The analysis of behavioural patterns from standardized video recordings of infants with varying degrees of visual impairment enables, via deep learning, classification of the infants by visual-impairment severity and by ophthalmological condition.
Go to the profile of Pep Pàmies
Pep Pàmies
Chief Editor, Nature Biomedical Engineering, Nature Research

Follow the Topic

Biotechnology
Life Sciences > Biological Sciences > Biotechnology

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

Explore this Collection

Medical Ultrasound: Emerging Techniques and Applications

This cross-journal Collection showcases the broad and exciting field of emerging techniques and applications in medical ultrasound.

Publishing Model: Hybrid

Deadline: Jan 29, 2027

Explore this Collection

Recommended Content

Cookie Settings

We use cookies to ensure the functionality of our website, to personalize content and advertising, to provide social media features, and to analyze our traffic. If you allow us to do so, we also inform our social media, advertising and analysis partners about your use of our website. You can decide for yourself which categories you want to deny or allow. Please note that based on your settings not all functionalities of the site are available.

Further information can be found in our privacy policy.

Cookie Control

Customise your preferences for any tracking technology

The following allows you to customize your consent preferences for any tracking technology used to help us achieve the features and activities described below. To learn more about how these trackers help us and how they work, refer to the cookie policy. You may review and change your preferences at any time.

Cookie policy Privacy policy
Always active, cannot be turned off
More information

These trackers are used for activities that are strictly necessary to operate or deliver the service you requested from us and, therefore, do not require you to consent.

More information

These trackers help us to deliver personalized marketing content and to operate, serve and track ads.

More information

These trackers help us to deliver personalized marketing content to you based on your behaviour and to operate, serve and track social advertising.

More information

These trackers help us to measure traffic and analyze your behaviour with the goal of improving our service.

More information

These trackers help us to provide a personalized user experience by improving the quality of your preference management options, and by enabling the interaction with external networks and platforms.