ReviewInternational ophthalmology clinics2024
Opportunities to Apply Human-centered Design in Health Care With Artificial Intelligence-based Screening for Diabetic Retinopathy.
Review in International ophthalmology clinics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Current perspectives and challenges of using artificial intelligence in immunodeficiencies.The Journal of allergy and clinical immunology · 2025Review
- Artificial intelligence applied to diabetes complications: a bibliometric analysis.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic retinopathy (DR) is a leading cause of blindness. Artificial intelligence (AI) has been proposed to provide a novel opportunity to increase screening for DR. While it is paramount to ensure AI has adequate technical capabilities to perform accurate screening, it is also important to assess how to best implement such technology into clinical practice. Human-centered design offers a methodology to understand the real-world context and behaviors of individuals, engage stakeholders, and rapidly prototype and test solutions, enhancing usability and avoiding unintended consequences. This review describes the methodology of human-centered design, examining how it has been used within a variety of health care contexts, with a particular focus on how it has been used to implement an AI-based DR screening program. Further research is needed to understand the best strategies to implement and evaluate AI in health care.
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What OpenQuestion holds
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.