Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms

This study successfully identified diagnosis-related ferroptosis genes in DKD and constructed an accurate diagnostic model. These findings enhance our understanding of the role of ferroptosis in DKD and may contribute to the development of new diagnostic and therapeutic approaches.

Authors

Institutions

Publication Details

Journal
Annals of Human Biology
Published
2025-04-02
DOI
https://doi.org/10.1080/03014460.2025.2477248
Citations
1
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
1.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms

Bo Xiang, Hongxia Liu, Wen Xiong, Guangyu Shang
1 citations
Annals of Human Biology
Ferroptosis and cancer prognosis
1.52
article

Identification of biomarkers related to iron death in diabetic kidney disease based on machine learning algorithms

Bo Xiang, Hongxia Liu, Wen Xiong, Guangyu Shang
article en
1 citations

Abstract

This study successfully identified diagnosis-related ferroptosis genes in DKD and constructed an accurate diagnostic model. These findings enhance our understanding of the role of ferroptosis in DKD and may contribute to the development of new diagnostic and therapeutic approaches.

Annals of Human BiologyVol. 52(1)
Jishou University (CN)
Good health and well-being
Openalex Percentile: Top 20%
Ferroptosis and cancer prognosis
1.52
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.