A simple and accessible diabetic retinopathy risk prediction model: Establishment and validation in a hospital-based cohort of type 2 diabetes patients

The proposed model shows promise for guiding early interventions and improving outcomes. Further external validation is needed to confirm its applicability across diverse populations.

Authors

Institutions

Publication Details

Journal
Diabetes Research and Clinical Practice
Published
2025-05-02
DOI
https://doi.org/10.1016/j.diabres.2025.112211
Citations
2
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
2.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A simple and accessible diabetic retinopathy risk prediction model: Establishment and validation in a hospital-based cohort of type 2 diabetes patients

Yawen Wang, Tianyi Zhang, Hui Liu, Juanjuan Gao
2 citations
Diabetes Research and Clinical Practice
Retinal Imaging and Analysis
2.72
article

A simple and accessible diabetic retinopathy risk prediction model: Establishment and validation in a hospital-based cohort of type 2 diabetes patients

Yawen Wang, Tianyi Zhang, Hui Liu, Juanjuan Gao
article en
2 citations

Abstract

The proposed model shows promise for guiding early interventions and improving outcomes. Further external validation is needed to confirm its applicability across diverse populations.

Diabetes Research and Clinical PracticeVol. 224
First Affiliated Hospital of Xi'an Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 11%
Retinal Imaging and Analysis
2.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.