CELM: An Ensemble Deep Learning Model for Early Cardiomegaly Diagnosis in Chest Radiography
<b>Background/Objectives:</b> Cardiomegaly—defined as the abnormal enlargement of the heart—is a key radiological indicator of various cardiovascular conditions. Early detection is vital for initiating timely clinical intervention and improving patient outcomes. This study investigates t...
Saved in:
| Main Authors: | Erdem Yanar, Fırat Hardalaç, Kubilay Ayturan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/15/13/1602 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PELM: A Deep Learning Model for Early Detection of Pneumonia in Chest Radiography
by: Erdem Yanar, et al.
Published: (2025-06-01) -
Evaluation of Cardiomegaly in Dogs Using the Manubrium Heart Score Method and Determination of Its Diagnostic Accuracy in Comparison with the Vertebral Heart Score
by: Bengü Bilgiç, et al.
Published: (2025-06-01) -
Investigating the diagnostic accuracy of vertebral heart score, vertebral left atrium score and thoracic width measurement in cats with suspected cardiac problems
by: B. Ozdil, et al.
Published: (2025-03-01) -
Role of Artificial Intelligence in Detecting Pneumothorax and Cardiomegaly in Chest X-rays: An Observational Study
by: Manasa Mayukha Hanumanthu, et al.
Published: (2025-05-01) -
Specialized Large Language Model Outperforms Neurologists at Complex Diagnosis in Blinded Case-Based Evaluation
by: Sami Barrit, et al.
Published: (2025-03-01)