Refined prognostication of pathological complete response in breast cancer using radiomic features and optimized InceptionV3 with DCE-MRI
Abstract Background Neoadjuvant therapy plays a pivotal role in breast cancer treatment, particularly for patients aiming to conserve their breast by reducing tumor size pre-surgery. The ultimate goal of this treatment is achieving a pathologic complete response (pCR), which signifies the complete e...
Saved in:
| Main Authors: | Satyabrata Pattanayak, Tripty Singh, Rishabh Kumar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-08565-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Parkinson’s disease detection using inceptionV3: A Deep learning approach
by: Pallavi M. Shanthappa, et al.
Published: (2025-06-01) -
SkinIncept: an ensemble transfer learning-based approach for multiclass skin disease classification using InceptionV3 and InceptionResNetV2
by: Md. Hasan Imam Bijoy, et al.
Published: (2025-05-01) -
Robust Deep Neural Network for Classification of Diseases from Paddy Fields
by: Karthick Mookkandi, et al.
Published: (2025-07-01) -
Enhancing book genre classification with BERT and InceptionV3: a deep learning approach for libraries
by: Xinting Yang, et al.
Published: (2025-06-01) -
Optimizing brain tumor detection in MRI scans through InceptionResNetV2 and deep stacked Autoencoders with SwiGLU activation and sparsity regularization
by: Vishal Awasthi, et al.
Published: (2025-06-01)