Improving healthcare sustainability using advanced brain simulations using a multi-modal deep learning strategy with VGG19 and bidirectional LSTM
BackgroundBrain tumor categorization on MRI is a challenging but crucial task in medical imaging, requiring high resilience and accuracy for effective diagnostic applications. This study describe a unique multimodal scheme combining the capabilities of deep learning with ensemble learning approaches...
Saved in:
| Main Authors: | Saravanan Chandrasekaran, S. Aarathi, Abdulmajeed Alqhatani, Surbhi Bhatia Khan, Mohammad Tabrez Quasim, Shakila Basheer |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-04-01
|
| Series: | Frontiers in Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1574428/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rice leaf disease classification using a fusion vision approach
by: B. Naresh kumar, et al.
Published: (2025-03-01) -
LightGBM-Based Human Action Recognition Using Sensors
by: Yinuo Liu, et al.
Published: (2025-06-01) -
GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis
by: Purushottam Pandey, et al.
Published: (2025-06-01) -
Predicting Live Weight for Female Rabbits of Meat Crosses From Body Measurements Using LightGBM, XGBoost and Support Vector Machine Algorithms
by: Hasan Önder, et al.
Published: (2025-01-01) -
Cultural Heritage Risk Assessment Based on Explainable Machine Learning Models: A Case Study of the Ancient Tea Horse Road in China
by: Hao Zhang, et al.
Published: (2025-03-01)