ReviewInternational journal of retina and vitreous2026
Artificial intelligence in retinal care: transforming the doctor-patient partnership.
Review in International journal of retina and vitreous, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- When the Algorithm Speaks First: Trust, Reliance and the Reconstruction of Clinical Metacognition.Journal of evaluation in clinical practice · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence into retinal practice represents more than a technological advancement; it constitutes an anthropological shift fundamentally redefining the centuries-old therapeutic partnership between physician and patient.
objectiveTo examine how artificial intelligence integration into retinal care transforms the therapeutic partnership, revealing what this transformation illuminates about the nature of medical knowledge itself and identifying frameworks for conscious implementation.
methodsWe conducted a structured narrative review examining AI-based diagnosis and monitoring of diabetic retinopathy and age-related macular degeneration (2018-2025), synthesizing clinical deployment evidence with qualitative implementation studies, adopting an anthropological interpretive stance to examine technology as a mediator of human relationships.
resultsFDA-approved AI systems demonstrate robust diagnostic performance for diabetic retinopathy and age-related macular degeneration. AI integration shifts encounters from examination-based to screen-mediated, clinical reasoning from individual to algorithm-guided, and physicians from diagnosticians to interpreters. Three insights emerge. First, AI reveals that medical practice always combined mechanistic reasoning with pattern recognition, now separated algorithmically. Second, accountability operates asymmetrically: while all stakeholders derive benefits from algorithmic integration, authority over system selection and deployment remains concentrated among vendors and institutions rather than distributed to frontline clinicians or patients. Third, impact diverges along existing stratification: transformation may create access for excluded populations while potentially eroding relationships for those who had comprehensive care, raising fundamental questions about equitable distribution.
conclusionsThe AI transformation of retinal care offers a revealing mirror of medicine's algorithmic future. Success demands epistemological rigor, robust evaluation competencies and establishing frameworks for shared accountability among the various stakeholders. Our framework maps six fundamental dimensions where synthesis supersedes substitution: expanding algorithmic capabilities while preserving healing relationships, creating access while maintaining continuity. Medicine can embrace algorithmic intelligence while preserving its humanistic core through conscious choices about epistemology, equity, and the character of practice we create.
Indexed as
Identifiers
What Socratic 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 Socratic graph.