Radiomics Analysis of Whole-Kidney Non-Contrast CT for Early Identification of Chronic Kidney Disease Stages 1–3

The NCCT-based radiomics model demonstrates significant clinical utility by enabling non-invasive, early diagnosis of CKD stages 1-3, outperforming radiologist assessments.

Authors

Institutions

Publication Details

Journal
Bioengineering
Published
2025-04-25
DOI
https://doi.org/10.3390/bioengineering12050454
Citations
5
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
3.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Radiomics Analysis of Whole-Kidney Non-Contrast CT for Early Identification of Chronic Kidney Disease Stages 1–3

Yuelang Zhang, Pan Zhang, Feng Shi, Dun Ding et al.
5 citations
Bioengineering
Advanced X-ray and CT Imaging
3.37
article

Radiomics Analysis of Whole-Kidney Non-Contrast CT for Early Identification of Chronic Kidney Disease Stages 1–3

Yuelang Zhang, Pan Zhang, Feng Shi, Dun Ding, Guirong Zhang, Yuwei Xia
article en
5 citations

Abstract

The NCCT-based radiomics model demonstrates significant clinical utility by enabling non-invasive, early diagnosis of CKD stages 1-3, outperforming radiologist assessments.

BioengineeringVol. 12(5)
Second Affiliated Hospital of Xi'an Jiaotong University (CN), United Imaging Healthcare (China) (CN)
Openalex Percentile: Top 8%
Advanced X-ray and CT Imaging
3.37
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.