Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of radiotherapy combined with chemotherapy in locally advanced cervical cancer

The model integrating DWI and clinical features has shown high value in non-invasive prediction of LRDM, which may aid in treatment and prognostication.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2025-10-08
DOI
https://doi.org/10.3389/fonc.2025.1668971
Citations
1
Primary Topic
Endometrial and Cervical Cancer Treatments
Type
article
Field-Weighted Citation Impact
2.06

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of radiotherapy combined with chemotherapy in locally advanced cervical cancer

Xiaoxia Ping, Nan Jiang, Xi Wang, Chunhong Hu et al.
1 citations
Frontiers in Oncology
Endometrial and Cervical Cancer Treatments
2.06
article

Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of radiotherapy combined with chemotherapy in locally advanced cervical cancer

Xiaoxia Ping, Nan Jiang, Xi Wang, Chunhong Hu, Qian Meng, Yuanqing Liu
article en
1 citations

Abstract

The model integrating DWI and clinical features has shown high value in non-invasive prediction of LRDM, which may aid in treatment and prognostication.

Frontiers in OncologyVol. 15
Soochow University (CN), First Affiliated Hospital of Soochow University (CN)
Government of Jiangsu Province
Openalex Percentile: Top 11%
Endometrial and Cervical Cancer Treatments
2.06
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.