ArticleInternational journal of retina and vitreous2019
Artificial intelligence, robotics and eye surgery: are we overfitted?
Article in International journal of retina and vitreous, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Artificial Intelligence in Ophthalmic Surgery: Current Applications and Expectations.Clinical ophthalmology (Auckland, N.Z.) · 2023Review
- Review
- Artificial intelligence and ophthalmic surgery.Current opinion in ophthalmology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Eye surgery, specifically retinal micro-surgery involves sensory and motor skill that approaches human boundaries and physiological limits for steadiness, accuracy, and the ability to detect the small forces involved. Despite assumptions as to the benefit of robots in surgery and also despite great development effort, numerous challenges to the full development and adoption of robotic assistance in surgical ophthalmology, remain. Historically, the first in-human-robot-assisted retinal surgery occurred nearly 30 years after the first experimental papers on the subject. Similarly, artificial intelligence emerged decades ago and it is only now being more fully realized in ophthalmology. The delay between conception and application has in part been due to the necessary technological advances required to implement new processing strategies. Chief among these has been the better matched processing power of specialty graphics processing units for machine learning. Transcending the classic concept of robots performing repetitive tasks, artificial intelligence and machine learning are related concepts that has proven their abilities to design concepts and solve problems. The implication of such abilities being that future machines may further intrude on the domain of heretofore "human-reserved" tasks. Although the potential of artificial intelligence/machine learning is profound, present marketing promises and hype exceeds its stage of development, analogous to the seventieth century mathematical "boom" with algebra. Nevertheless robotic systems augmented by machine learning may eventually improve robot-assisted retinal surgery and could potentially transform the discipline. This commentary analyzes advances in retinal robotic surgery, its current drawbacks and limitations, and the potential role of artificial intelligence in robotic retinal surgery.
Indexed as
Identifiers
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.