2023
DOI: 10.1016/j.clinsp.2023.100210
|View full text |Cite
|
Sign up to set email alerts
|

Deep learning for diagnosis of malign pleural effusion on computed tomography images

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 52 publications
0
1
0
Order By: Relevance
“…Imaging techniques: Advances in imaging techniques, particularly magnetic resonance imaging and computed tomography, represent significant strides in enhancing diagnostic capabilities when it comes to pleural effusions [ 35 , 36 ]. The improved image quality afforded by these technologies enables healthcare professionals to visualize pleural abnormalities with greater clarity and precision.…”
Section: Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…Imaging techniques: Advances in imaging techniques, particularly magnetic resonance imaging and computed tomography, represent significant strides in enhancing diagnostic capabilities when it comes to pleural effusions [ 35 , 36 ]. The improved image quality afforded by these technologies enables healthcare professionals to visualize pleural abnormalities with greater clarity and precision.…”
Section: Reviewmentioning
confidence: 99%
“…Computer-aided diagnostic analysis: Computer-aided diagnostic analysis has revolutionized the field of pleural diseases, specifically identifying cancer cells in pleural fluid [ 35 ]. Deep learning algorithms, trained with CT image data, demonstrate promising adequacies in discerning characteristics and diagnostic criteria for pleural effusion diagnosis.…”
Section: Reviewmentioning
confidence: 99%
“…In recent years, noninvasive imaging modalities such as ultrasonography (US) and computed tomography (CT) have become increasingly important in evaluating pleural effusions and diagnosing MPE. These modalities can provide valuable information about the nature and characteristics of pleural effusion, potentially guiding clinical decision making and reducing the need for invasive procedures [7][8][9].…”
Section: Introductionmentioning
confidence: 99%