ArticleNature medicine2023
Early detection of visual impairment in young children using a smartphone-based deep learning system.
Article in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 5 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- Evaluating the Quality and Features of Visual Acuity Apps Using the Mobile App Rating Scale: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- Systematic review and meta-analysis of artificial intelligence models for strabismus screening: methodological insights and future directions.International journal of surgery (London, England) · 2025Pooled it
- Transformative applications of oculomics-based AI approaches in the management of systemic diseases: A systematic review.Journal of advanced research · 2025Pooled it
- Effectiveness of smartphone technology for detection of paediatric ocular diseases-a systematic review.BMC ophthalmology · 2025Pooled it
- A scoping review of the feasibility, usability, and efficacy of digital interventions in older adults concerning physical activity and/or exercise.Frontiers in aging · 2025Pooled it
- Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial.JAMA ophthalmology · 2026Trial
- Risk factors and critical thresholds for glucocorticoid-induced ocular adverse reactions in children: implications for muscle and neuromuscular disease management.European journal of translational myology · 2026Article
- ProptoView: AI-based digital exophthalmometry using multi-view facial images in a multinational validation study.Journal of translational medicine · 2026Article
- Evaluation of a Novel Autostereoscopic Three-Dimensional System for Binocular Visual Function: A Comparative Validation Study.Journal of clinical medicine · 2026Article
- From blink to care: smartphone video-based functional analysis and personalized management in pediatric blepharoptosis.NPJ digital medicine · 2026Article
- Validated semi-supervised early and accurate screening for anterior segment diseases: a 3PM-guided conceptual and technological innovation.The EPMA journal · 2026Article
- Sustainable Ophthalmology Applications: From the Perspective of Strabismus and Pediatric Ophthalmology.Turkish journal of ophthalmology · 2026Review
- Smartphone applications for early screening of retinoblastoma: a scoping review.BMC ophthalmology · 2026Article
- Transparency of medical artificial intelligence systems.Nature reviews bioengineering · 2026Article
- Recommended practices for vision screening in pre-school-age children: A 2025 update.Optometry and vision science : official publication of the American Academy of Optometry · 2025Review
- Digital technologies in enhancing hierarchical vision health management for the next 1000 days of children's life: multi-component economic evaluation.The Lancet regional health. Western Pacific · 2025Article
- Ophthalmic drug discovery and development using artificial intelligence and digital health technologies.NPJ digital medicine · 2025Review
- Article
- Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer.BMC medical imaging · 2025Article
- Telemedicine in ophthalmology.Wiener medizinische Wochenschrift (1946) · 2025Review
Corrections and comments
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Authors and funding
54 authors at 13 institutions in 5 countries.
Funding
Abstract
Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and ocular movements, can assist ophthalmic practice, applying these features to real-world screening remains challenging. Here, we present a mobile health (mHealth) system, the smartphone-based Apollo Infant Sight (AIS), which identifies visually impaired children with any of 16 ophthalmic disorders by recording and analyzing their gazing behaviors and facial features under visual stimuli. Videos from 3,652 children (≤48 months in age; 54.5% boys) were prospectively collected to develop and validate this system. For detecting visual impairment, AIS achieved an area under the receiver operating curve (AUC) of 0.940 in an internal validation set and an AUC of 0.843 in an external validation set collected in multiple ophthalmology clinics across China. In a further test of AIS for at-home implementation by untrained parents or caregivers using their smartphones, the system was able to adapt to different testing conditions and achieved an AUC of 0.859. This mHealth system has the potential to be used by healthcare professionals, parents and caregivers for identifying young children with visual impairment across a wide range of ophthalmic disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.