Evidence map›Paper›PMID 42814183›Full record

ReviewInternational ophthalmology2026

Artificial intelligence in cataract management: current status and future perspectives.

Zizhuo Zhao, Manlu Huang

Abstract readReview
PubMed Publisher
In one paragraph

Review in International ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zizhuo ZhaoDepartment of Ophthalmology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, Hebei, China. 1850822893@qq.com.ORCID https://orcid.org/0009-0005-6782-0526
Manlu HuangDepartment of Ophthalmology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo summarize recent advances in artificial intelligence (AI) applications across the entire cataract management pathway and to discuss current challenges and future directions.

methodsWe conducted a narrative mini review of studies published since 2021 on AI applications in cataract diagnosis and screening, intraocular lens (IOL) power calculation, intraoperative guidance, and postoperative management, with emphasis on deep learning and emerging technologies.

resultsAI models have achieved expert-level performance in automated cataract detection and grading from slit-lamp images, with pooled AUC values approaching 0.99 in meta-analyses. AI-based IOL power calculation formulas have shown superior accuracy compared with traditional formulas, especially in challenging cases such as highly myopic eyes. Intraoperatively, AI systems can recognize surgical phases and track instruments with high accuracy, supporting surgical training and quality assessment. Postoperatively, multimodal AI models integrating imaging and clinical data have improved the prediction of visual outcomes and complications. Emerging technologies, including large language models, portable smartphone-based screening devices, and multimodal prediction models, represent promising new directions, although challenges related to data generalizability, algorithm interpretability, and clinical translation remain to be addressed.

conclusionAI has the potential to significantly improve the efficiency, accuracy, and accessibility of cataract care, but should serve as an assistive tool rather than a replacement for clinical judgment.

Indexed as

Artificial IntelligenceCataractCataract ExtractionHumansLenses, IntraocularArtificial intelligenceCataractCataract surgeryDeep learningIntraocular lensPosterior capsule opacificationTelemedicine

Identifiers

What OpenQuestion holds

Textmetadata
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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.