A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study

This study showed the feasibility and effectiveness of CNN model combing CT images and CTCs levels in predicting the diagnosis of mediastinal lesions. It could serve as a useful method to assist thoracic surgeons in improving diagnostic accuracy and has the potential to make management decisions.

Authors

Institutions

Publication Details

Journal
BMC Medicine
Published
2025-05-07
DOI
https://doi.org/10.1186/s12916-025-04104-z
Citations
4
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
6.07
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study

Minwei Bao, Feng Wang, Guangxue Wang, Fan Yang et al.
4 citations
BMC Medicine
Lung Cancer Diagnosis and Treatment
6.07
article

A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study

Minwei Bao, Feng Wang, Guangxue Wang, Fan Yang, Lei Zhu, Tao Bo
article en
4 citations

Abstract

This study showed the feasibility and effectiveness of CNN model combing CT images and CTCs levels in predicting the diagnosis of mediastinal lesions. It could serve as a useful method to assist thoracic surgeons in improving diagnostic accuracy and has the potential to make management decisions.

BMC MedicineVol. 23(1)
Tongji University (CN), Shanghai Pulmonary Hospital (CN), Shanghai East Hospital (CN)
Good health and well-being
Openalex Percentile: Top 4%
Lung Cancer Diagnosis and Treatment
6.07
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.

A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study — Minwei Bao, Feng Wang, et al. · BMC Medicine (2025) | TGRS Research Map | TGRS