Data-Driven Clinical Decision-Making Using Deep Learning in Imaging
| 企業作者: | |
|---|---|
| 其他作者: | , |
| 總結: | XII, 274 p. 105 illus., 92 illus. in color. text |
| 語言: | 英语 |
| 出版: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
|
| 版: | 1st ed. 2024. |
| 叢編: | Studies in Big Data,
152 |
| 主題: | |
| 在線閱讀: | https://doi.org/10.1007/978-981-97-3966-0 |
| 格式: | 電子 電子書 |
書本目錄:
- Improved Classification of Kidney Lesions in CT scans using CNN with Attention Layers: Achieving High Accuracy and Performance
- Domain Adaptation in Medical Imaging: Evaluating the Effectiveness of Transfer Learning
- Elevating Breast Cancer Research: Discovering New Frontiers with Attention-Based U-Net Architecture for Segmentation
- Early Skin Cancer Detection in Computer Vision: Leveraging Attention-Based Deep Ensembles
- Incorporating Residual Connections into a Multi-Channel CNN for Interpretable Lung Cancer Detection in Digital Pathology
- Privacy Preserving Breast Cancer Risk Prediction with Mammography Images Using Federated Learning
- Federated Learning for Scabies Recognition: A Privacy-Preserving Approach
- An Improved Transfer Learning based Approach for the Classification of Multi-Stage HER2 Breast Cancer from Hematoxylin and Eosin Images
- Unveiling the Unique Dermatological Signatures of Human Monkeypox, Chickenpox, and Measles through Deep Transfer Learning Model
- Development of a Deep Learning Framework for Brain Tumors Classification Using Transfer Learning
- Featured-based brain tumor image registration using a Fussy-clustering segmentation approach
- Enhancing Breast Cancer Detection Systems: Augmenting and Upscaling Mammogram Images using Generative Adversarial Networks
- A Deep Learning Approach Bone Marrow Cancer Cell Multiclass Classification using Microscopic Images
- Detecting Skin Cancer Through the Utilization of Deep Convolutional Neural Networks and Generative Adversarial Networks.