To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery using machine learning techniques and to explore the role of multifeature fusion. Data from 137 breast cancer postoperative patients with new nodules...
Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully el...
Journal of medical engineering & technology
Feb 14, 2025
Present work involves rigorous experimentation for classification of mammographic masses by employing four deep transfer learning models using hierarchical framework. Experimental work is carried on 518 SFM images of DDSM dataset with 208, 150 and 16...
International journal of medical informatics
Feb 13, 2025
OBJECTIVES: While prior machine learning (ML) models for cancer survivability prediction often treated all cancer stages uniformly, cancer survivability prediction should involve understanding how different stages impact the outcomes. Additionally, t...
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Feb 13, 2025
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.
Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approac...
PURPOSE: This study aimed to assess the image quality and the diagnostic value of deep learning reconstruction (DLR) for diffusion-weighted imaging (DWI) compared with conventional single-shot echo-planar imaging (ss-EPI) in 3 T breast MRI.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 12, 2025
PURPOSE: The aim of this work is to compare different machine learning models for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer using radiomics features from dynamic contrast-enhanced magnetic reso...
We developed an automatic method based on a convolutional neural network (CNN) that identifies metastatic lesions in whole slide images (WSI) of intraoperative frozen sections from sentinel lymph nodes in breast cancer. A total of 954 sentinel lymph ...
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...