Prediction and Risk Factor Analysis of in-Stent Restenosis and Revascularization after Coronary Stenting Based on Machine Learning

We successfully constructed a predictive and risk factor analysis model for in-stent restenosis and revascularization following coronary stent implantation. This model may be helpful for clinical decision-making.

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Publication Details

Journal
Cardiology
Published
2025-07-12
DOI
https://doi.org/10.1159/000547438
Primary Topic
Coronary Interventions and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
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article

Prediction and Risk Factor Analysis of in-Stent Restenosis and Revascularization after Coronary Stenting Based on Machine Learning

Hao Ling, Chunli Song
Cardiology
Coronary Interventions and Diagnostics
article

Prediction and Risk Factor Analysis of in-Stent Restenosis and Revascularization after Coronary Stenting Based on Machine Learning

Hao Ling, Chunli Song
article en

Abstract

We successfully constructed a predictive and risk factor analysis model for in-stent restenosis and revascularization following coronary stent implantation. This model may be helpful for clinical decision-making.

Cardiology
Second Affiliated Hospital of Jilin University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 71%
Coronary Interventions and Diagnostics
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Prediction and Risk Factor Analysis of in-Stent Restenosis and Revascularization after Coronary Stenting Based on Machine Learning — Hao Ling, Chunli Song · Cardiology (2025) | TGRS Research Map | TGRS