Evidence map›Paper›PMID 39903164›Full record

ArticleTranslational vision science & technology2025

Advanced Artificial-Intelligence-Based Jiang Formula for Intraocular Lens Power in Congenital Ectopia Lentis.

Yan Liu, Xinyue Wang, Linghao Song, Yang Sun, Zexu Chen, Wannan Jia, Xin Shen, Yalei Wang, Xinyao Chen, Qiuyi Huo and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational vision science & technology, 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

13 authors.

Yan LiuEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Xinyue WangEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Linghao SongEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Yang SunEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Zexu ChenEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Wannan JiaEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Xin ShenEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Yalei WangEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Xinyao ChenEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Qiuyi HuoEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Pranav Prakash EdaviShanghai Medical College (SHMC), Fudan University, Shanghai, China.
Tianhui ChenEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.
Yongxiang JiangEye Institute and Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The purpose of this study was to develop an artificial intelligence (AI)-based intraocular lens (IOLs) power calculation formula for improving the accuracy of IOLs power calculations in patients with congenital ectopia lentis (CEL). Methods: A total of 651 eyes with CEL that underwent IOLs implantation surgery were included in this study. An AI-based ensemble formula-the Jiang Formula, was developed using a training dataset of 520 eyes and evaluated on a testing dataset of 131 eyes. A five-fold cross-validation and a two-layer ensemble learning model were constructed. The formula was then tested in a test set and compared against five current classic formulas. Results: The cohort included young patients (mean age = 14.38 ± 13.35 years). The Jiang Formula showed the lowest prediction error (PE; = 0.08 ± 1.01 diopters [D]), absolute error (AE; = 0.77 ± 0.65 D), median absolute error (MedAE; = 0.66 D), and root mean square error (RMSE; = 1.02 D) among six formulas (P < 0.001). Moreover, 68.00% of the eyes in the test set had AE within 1.0 D in the Jiang Formula. Conclusions: AI-integrated two-layer ensemble learning model demonstrates promising applications in IOLs power calculations for patients with CEL, not only providing higher predictive accuracy than current classic formulas but also accommodating extreme values and variations in surgical techniques. Translational Relevance: The Jiang Formula, an AI-integrated two-layer ensemble learning model, enhances IOLs power calculation accuracy in patients with CEL, ultimately improving surgical outcomes and supporting more effective, personalized treatment in this unique patient group.

Indexed as

Artificial IntelligenceEctopia LentisLenses, IntraocularLens Implantation, IntraocularOptics and PhotonicsAdolescentAdultChildFemaleHumansMaleRefraction, OcularVisual AcuityYoung Adult

Identifiers

PMID39903164
PMCPMC11801393

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.