AIMC Topic: Breast Neoplasms

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The role of an artificial intelligence software in clinical senology: a mammography multi-reader study.

La Radiologia medica
PURPOSE: To evaluate the diagnostic role of a dedicated AI software in detecting anomalous breast findings on mammography and tomosynthesis images in the clinical setting, stand-alone and as aid of four readers.

Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.

Journal of cancer survivorship : research and practice
PURPOSE: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim ...

Clinical evaluation of deep learning and atlas-based auto-segmentation for organs at risk delineation.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Manual delineation of organs at risk and clinical target volumes is essential in radiotherapy planning. Atlas-based auto-segmentation (ABAS) algorithms have become available and been shown to provide accurate contouring for various anatomical sites. ...

Deep learning-enabled breast cancer endocrine response determination from H&E staining based on ESR1 signaling activity.

Scientific reports
Estrogen receptor (ER) positivity by immunohistochemistry has long been a main selection criterium for breast cancer patients to be treated with endocrine therapy. However, ER positivity might not directly correlate with activated ER signaling activi...

Deviation-support based fuzzy ensemble of multi-modal deep learning classifiers for breast cancer prognosis prediction.

Scientific reports
Breast cancer is the fifth leading cause of death in females worldwide. Early detection and treatment are crucial for improving health outcomes and preventing more serious conditions. Analyzing diverse information from multiple sources without errors...

Artificial intelligence in breast imaging: potentials and challenges.

Physics in medicine and biology
Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, including neoadjuvant chemotherapy, surgery, postoperative chemotherapy, targeted therapy, endocrine ...

Mechanisms of Exercise Intolerance Across the Breast Cancer Continuum: A Pooled Analysis of Individual Patient Data.

Medicine and science in sports and exercise
PURPOSE: The purpose of this study is to evaluate the prevalence of abnormal cardiopulmonary responses to exercise and pathophysiological mechanism(s) underpinning exercise intolerance across the continuum of breast cancer (BC) care from diagnosis to...

Saliency of breast lesions in breast cancer detection using artificial intelligence.

Scientific reports
The analysis of mammograms using artificial intelligence (AI) has shown great potential for assisting breast cancer screening. We use saliency maps to study the role of breast lesions in the decision-making process of AI systems for breast cancer det...

Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis.

BMC cancer
BACKGROUND: This study aimed to comprehensively evaluate the accuracy and effect of computed tomography (CT) and magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithms for predicting lymph node metastasis in breast cancer p...