The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT

There was no significant difference between the diagnosis results of the proposed DL-based method and the radiologists' diagnostic approach in differentiating benign and malignant lung nodules on spiral CT (P< 0.05).

Authors

Institutions

Publication Details

Journal
Technology and Health Care
Published
2024-11-08
DOI
https://doi.org/10.3233/thc-241079
Citations
2
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.84

Funders

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

The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT

Bangquan Liu, Yonggang Zhao, Dongquan Liu
2 citations
Technology and Health Care
Lung Cancer Diagnosis and Treatment
0.84
article

The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT

Bangquan Liu, Yonggang Zhao, Dongquan Liu
article en
2 citations

Abstract

There was no significant difference between the diagnosis results of the proposed DL-based method and the radiologists' diagnostic approach in differentiating benign and malignant lung nodules on spiral CT (P< 0.05).

Technology and Health CareVol. 32(6)
Ningbo University (CN), Ninghai County First Hospital (CN)
Ningbo University, Natural Science Foundation of Ningbo
Openalex Percentile: Top 23%
Lung Cancer Diagnosis and Treatment
0.84
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.