Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm
One of the forms of cancerous tumors that can be fatal is malignant lymphoma. Histopathological examination of lymphoma tissue images is a diagnostic technique for detecting malignant lymphomas. Differentiating lymphoma subtypes manually is challenging due to their similar morphological features. Th...
Saved in:
| Main Authors: | Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11018333/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimized DenseNet Architectures for Precise Classification of Edible and Poisonous Mushrooms
by: Jay Prakash Singh, et al.
Published: (2025-06-01) -
Enhanced DL-Based Breast Cancer Diagnosis and Classification Using Modified DenseNet-121, DenseNet-201, and MobileNetV2: Optimized Architectures and Refined Activation Functions
by: Khaddouj Taifi, et al.
Published: (2025-01-01) -
A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet
by: Muhammad Waqas Ahmed, et al.
Published: (2025-01-01) -
Identification Method of Mature Wheat Varieties Based on Improved DenseNet Model
by: Zihang Liu, et al.
Published: (2025-03-01) -
DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification
by: Musa Adamu Wakili, et al.
Published: (2025-01-01)