Data-Driven Clinical Decision-Making Using Deep Learning in Imaging
| Автор-организация: | |
|---|---|
| Другие авторы: | , |
| Примечания: | XII, 274 p. 105 illus., 92 illus. in color. text |
| Язык: | английский |
| Опубликовано: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
|
| Издание: | 1st ed. 2024. |
| Серии: | Studies in Big Data,
152 |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/978-981-97-3966-0 |
| Формат: | Электронный ресурс Книга |
Оглавление:
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- 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.