AIMC Topic: Breast Neoplasms
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Deep learning-driven prediction in healthcare systems: Applying advanced CNNs for enhanced breast cancer detection.
Computers in biology and medicine
Feb 27, 2025
The mortality risk associated with breast cancer is experiencing an exponential rise, underscoring the critical importance of early detection. It is the primary cause of mortality among women under 50 and ranks as the second deadliest disease globall...
Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.
Breast cancer research : BCR
Feb 27, 2025
OBJECTIVE: The aim of this study was to develop and validate a deep learning radiomics (DLR) model based on longitudinal ultrasound data and clinical features to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breas...
Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer.
Frontiers in endocrinology
Feb 27, 2025
OBJECTIVE: This study explores the value of combining intratumoral and peritumoral radiomics features from ultrasound imaging with clinical characteristics to assess axillary lymph node burden in breast cancer patients.
Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer.
Oncogene
Feb 26, 2025
CDK4/6 inhibitors in combination with endocrine therapy are widely used to treat HR+/HER2- metastatic breast cancer leading to improved progression-free survival (PFS) compared to single agent endocrine therapy. Over 300 patients receiving standard-o...
Machine Learning-Aided Intelligent Monitoring of Multivariate miRNA Biomarkers Using Bipolar Self-powered Sensors.
ACS nano
Feb 26, 2025
Breast cancer has become the most prevalent form of cancer among women on a global scale. The early and timely diagnosis of breast cancer is of the utmost importance for improving the survival rate of patients with this disease. The occurrence of bre...
Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes.
Frontiers in immunology
Feb 26, 2025
BACKGROUND: Breast cancer, a highly prevalent global cancer, poses significant challenges, especially in advanced stages. Prognostic models are crucial to enhance patient outcomes. Tertiary lymphoid structures (TLS) within the tumor microenvironment ...
Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast.
PloS one
Feb 26, 2025
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...
AI in Breast Cancer Imaging: An Update and Future Trends.
Seminars in nuclear medicine
Feb 25, 2025
Breast cancer is one of the most common types of cancer affecting women worldwide. Artificial intelligence (AI) is transforming breast cancer imaging by enhancing diagnostic capabilities across multiple imaging modalities including mammography, digit...
Impact of an artificial intelligence decision support system among radiologists with different levels of experience in breast ultrasound: A prospective study in a tertiary center.
European journal of radiology
Feb 25, 2025
PURPOSE: To assess the impact of an artificial intelligence decision support system (Koios DS) on the diagnostic performance of radiologists with different experience in breast ultrasound and to evaluate its potential to reduce unnecessary biopsies.
Decoding breast cancer imaging trends: the role of AI and radiomics through bibliometric insights.
Breast cancer research : BCR
Feb 25, 2025
BACKGROUND: Radiomics and AI have been widely used in breast cancer imaging, but a comprehensive systematic analysis is lacking. Therefore, this study aims to conduct a bibliometrics analysis in this field to discuss its research status and frontier ...
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