Interpretable Deep Learning for Pneumonia Detection Using Chest X-Ray Images
Pneumonia remains a global health issue, creating the need for accurate detection methods for effective treatment. Deep learning models like ResNet50 show promise in detecting pneumonia from chest X-rays; however, their black-box nature limits the transparency, which fails to meet that needed for cl...
Saved in:
| Main Authors: | Jovito Colin, Nico Surantha |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/1/53 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An interpretable physics-informed deep learning model for estimating multiple air pollutants
by: Binjie Chen, et al.
Published: (2025-12-01) -
Decoding Human Facial Emotions: A Ranking Approach Using Explainable AI
by: Sudheer Babu Punuri, et al.
Published: (2024-01-01) -
Diagnosis of pneumonia from chest X-ray images using YOLO deep learning
by: Yanchun Xie, et al.
Published: (2025-04-01) -
Conformal deep forest for uncertainty-aware classification
by: Jing Zhang, et al.
Published: (2025-08-01) -
Comparing Ultrasound, Chest X-Ray, and CT Scan for Pneumonia Detection
by: Al Nufaiei ZF, et al.
Published: (2025-03-01)