Preoperative CT radiomics<b>-</b>based model for predicting Ki<b>-</b>67 expression in clear cell renal cell carcinoma patients.

A CT radiomics-based model for predicting Ki-67 expression in ccRCC was successfully developed. This model provides valuable guidance for treatment planning and prognostic assessment in ccRCC patients.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2024-11-28
DOI
https://doi.org/10.11817/j.issn.1672-7347.2024.240455
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preoperative CT radiomics-based model for predicting Ki-67 expression in clear cell renal cell carcinoma patients.

Jia‐Yi Wang, Yunfeng Zhang, Fenghai Zhou, Han He et al.
PubMed
Radiomics and Machine Learning in Medical Imaging
article

Preoperative CT radiomics-based model for predicting Ki-67 expression in clear cell renal cell carcinoma patients.

Jia‐Yi Wang, Yunfeng Zhang, Fenghai Zhou, Han He, Wenbo Zhang, Zhijun Yang
article en

Abstract

A CT radiomics-based model for predicting Ki-67 expression in ccRCC was successfully developed. This model provides valuable guidance for treatment planning and prognostic assessment in ccRCC patients.

PubMedVol. 49(11)
Gansu University of Traditional Chinese Medicine (CN), Gansu Provincial Hospital (CN), First Hospital of Lanzhou University (CN), Lanzhou University (CN)
Openalex Percentile: Top 56%
Radiomics and Machine Learning in Medical Imaging
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.