Evidence map›Paper›PMID 41095953›Full record

ArticleJournal of clinical medicine2025

Oculoplastics and Augmented Intelligence: A Literature Review.

Edsel Ing, Mostafa Bondok

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Edsel IngDepartment of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada.ORCID 0000-0003-0623-0934
Mostafa BondokSection of Ophthalmology, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada.ORCID 0000-0002-7567-8962

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) and augmented intelligence have significant potential in oculoplastics, offering tools for diagnosis, treatment recommendations, and administrative efficiency. This article discusses current and potential applications of AI in ptosis, eyelid and conjunctival cancer, thyroid-associated orbitopathy (TAO), giant cell arteritis (GCA), and orbital fractures. AI-based programs can assist in screening, predicting surgical outcomes, and improving patient care through data-driven decisions. Privacy concerns, particularly with the use of facial and ocular photographs, require robust solutions, including blockchain, federated learning and steganography. Large generalizable datasets with adequate validation are crucial for future AI development. While AI can assist in clinical decision-making and administrative tasks, physician oversight remains critical to prevent potential errors. Large language models like ChatGPT also have the potential to counsel patients, although further validation is needed to ensure accuracy and patient safety. Ultimately, AI should be regarded as an augmentative tool that supports, rather than replaces, physician expertise in oculoplastic care.

Indexed as

artificial intelligenceaugmented intelligenceeyelid neoplasmsgiant cell arteritislarge language modelsmachine learningoculoplasticsorbital fracturesptosisthyroid eye disease

Identifiers

PMID41095953
PMCPMC12524889

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.