Evidence map›Paper›PMID 41902122›Full record

ArticleSensors (Basel, Switzerland)2026

Prediction of Cataract Severity Using Slit Lamp Images from a Portable Smartphone Device: A Pilot Study.

David Z Chen, Changshuo Liu, Junran Wu, Lei Zhu, Beng Chin Ooi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

5 authors.

David Z ChenDepartment of Ophthalmology, National University Hospital, Singapore 119024, Singapore.ORCID 0000-0002-2153-3100
Changshuo LiuDepartment of Computer Science, National University of Singapore, Singapore 117417, Singapore.ORCID 0009-0007-3879-9814
Junran WuDepartment of Computer Science, National University of Singapore, Singapore 117417, Singapore.ORCID 0000-0001-6742-4332
Lei ZhuDepartment of Computer Science, National University of Singapore, Singapore 117417, Singapore.ORCID 0000-0002-9193-8234
Beng Chin OoiSchool of Software Technology, Zhejiang University, Ningbo 315100, China.

Funding

National University Health System NUHSRO/2022/RO5+6/SPIN/02
6 · The paper itself

Abstract

Cataract diagnosis requires a comprehensive dilated examination by an ophthalmologist using a slit lamp; there is currently no effective means to objectively screen for cataracts in the community using portable devices without dilation. We hypothesized that it would be possible to predict cataract severity using deep learning on images taken using a portable smartphone-based slit lamp prototype, with and without dilation. In this prospective cross-sectional pilot study, slit lamp images were captured from eligible patients with cataracts in a tertiary clinic using a portable slit lamp prototype attached to a smartphone. The Pentacam nuclear staging score (PNS, Pentacam

Indexed as

CataractSlit LampSmartphoneAdultAgedAged, 80 and overCross-Sectional StudiesDeep LearningFemaleHumansMaleMiddle AgedPilot ProjectsProspective Studiescataractdeep learningremote monitoringscreeningteleophthalmology

Identifiers

PMID41902122
PMCPMC13030526

What OpenQuestion holds

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LicenceCC BY
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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.