AIMC Topic: Breast Neoplasms

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Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.

Physics in medicine and biology
In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally ...

Machine learning to parse breast pathology reports in Chinese.

Breast cancer research and treatment
INTRODUCTION: Large structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics communi...

Deep Convolutional Neural Networks for breast cancer screening.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Radiologists often have a hard time classifying mammography mass lesions which leads to unnecessary breast biopsies to remove suspicions and this ends up adding exorbitant expenses to an already burdened patient and health c...

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis.

Radiological physics and technology
Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and i...

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.

The British journal of radiology
OBJECTIVE: To train a generic deep learning software (DLS) to classify breast cancer on ultrasound images and to compare its performance to human readers with variable breast imaging experience.

Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.

Physics in medicine and biology
Breast density is one of the most significant factors that is associated with cancer risk. In this study, our purpose was to develop a supervised deep learning approach for automated estimation of percentage density (PD) on digital mammograms (DMs). ...

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

Computational and mathematical methods in medicine
Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The inv...

Comparison of Changes in the Lipid Profiles of Eastern Chinese Postmenopausal Women With Early-Stage Breast Cancer Treated With Different Aromatase Inhibitors: A Retrospective Study.

Clinical pharmacology in drug development
Cardiovascular morbidity is closely associated with serum lipid level. We aimed to investigate the effects of different aromatase inhibitors, including letrozole, anastrozole, and exemestane, on the lipid profile of eastern Chinese breast cancer pati...

L1 Cell Adhesion Molecule and Its Soluble Form sL1 Exhibit Poor Prognosis in Primary Breast Cancer Patients.

Clinical breast cancer
INTRODUCTION: The L1 cell adhesion molecule (L1-CAM) and its soluble form sL1 play a prominent role in invasion and metastasis in several cancers. However, its association with breast cancer is still unclear.

HCV nonstructural protein 4 is associated with aggressiveness features of breast cancer.

Breast cancer (Tokyo, Japan)
BACKGROUND: Hepatitis C virus (HCV) has the lymphotropic feature that is supposed to be the reason of related extrahepatic manifestation. HCV viral oncoproteins may participate in the regulation of some gene expression that has been implicated in tum...