AI Medical Compendium Topic:
Breast Neoplasms

Clear Filters Showing 601 to 610 of 2037 articles

Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.

Cancer medicine
BACKGROUND: Current methods utilizing preoperative magnetic resonance imaging (MRI)-based radiomics for assessing lymphovascular invasion (LVI) in patients with early-stage breast cancer lack precision, limiting the options for surgical planning.

MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC...

Artificial Intelligence for Breast Cancer Detection on Mammography: Factors Related to Cancer Detection.

Academic radiology
RATIONALE AND OBJECTIVES: Little is known about the factors affecting the Artificial Intelligence (AI) software performance on mammography for breast cancer detection. This study was to identify factors associated with abnormality scores assigned by ...

Use of Health Belief Model-based Deep Learning to Understand Public Health Beliefs in Breast Cancer Screening from Social Media before and during the COVID-19 Pandemic.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Breast cancer is the second leading cause of cancer death for women in the United States. While breast cancer screening participation is the most effective method for early detection, screening rate has remained low. Given that understanding health p...

Enhancing Ki-67 Prediction in Breast Cancer: Integrating Intratumoral and Peritumoral Radiomics From Automated Breast Ultrasound via Machine Learning.

Academic radiology
RATIONALE AND OBJECTIVES: Traditional Ki-67 evaluation in breast cancer (BC) via core needle biopsy is limited by repeatability and heterogeneity. The automated breast ultrasound system (ABUS) offers reproducibility but is constrained to morphologica...

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields, including healthcare. This case study reports on the first use of LMM in a pretreatment discussion ...

Intersectional analysis of inequalities in self-reported breast cancer screening attendance using supervised machine learning and PROGRESS-Plus framework.

Frontiers in public health
BACKGROUND: Breast cancer is a critical public health concern in Spain, and organized screening programs have been in place since the 1990s to reduce its incidence. However, despite the bi-annual invitation for breast cancer screening (BCS) for women...

Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History.

Computer methods in biomechanics and biomedical engineering
Breast cancer poses a significant global health challenge, demanding enhanced diagnostic accuracy and streamlined medical history documentation. This study presents a holistic approach that harnesses the power of artificial intelligence (AI) and mach...

Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes.

Annals of clinical and laboratory science
OBJECTIVE: Deep learning has been shown to be useful in detecting breast cancer metastases by analyzing whole slide images (WSI) of sentinel lymph nodes; however, it requires extensive analysis of all the lymph node slides. Our deep learning study at...