AIMC Topic: Breast Neoplasms

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Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning.

Journal of digital imaging Feb 1, 2019
Breast cancer is a leading cause of cancer death among women in the USA. Screening mammography is effective in reducing mortality, but has a high rate of unnecessary recalls and biopsies. While deep learning can be applied to mammography, large-scale...
Mammography Breast Image Interpretation, Computer-Assisted Breast Neoplasms Middle Aged Deep Learning Humans Databases, Factual Electronic Health Records Female
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Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement.

Journal of digital imaging Feb 1, 2019
The aim of this study is to develop a fully automated convolutional neural network (CNN) method for quantification of breast MRI fibroglandular tissue (FGT) and background parenchymal enhancement (BPE). An institutional review board-approved retrospe...
Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Breast Image Interpretation, Computer-Assisted Neural Networks, Computer Retrospective Studies Female Breast Neoplasms
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[Establishment of a deep feature-based classification model for distinguishing benign and malignant breast tumors on full-filed digital mammography].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Jan 30, 2019
OBJECTIVE: To develop a deep features-based model to classify benign and malignant breast lesions on full- filed digital mammography.
Deep Learning Mammography Female Breast Neoplasms Diagnosis, Computer-Assisted Humans
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Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data.

Folia biologica Jan 1, 2019
Breast cancer survival prediction can have an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict the survival prospects of patients, but newer algorith...
Neural Networks, Computer Female Aged Aged, 80 and over Humans Survival Analysis Calibration Demography Middle Aged Deep Learning Support Vector Machine Decision Trees Young Adult Adult Breast Neoplasms
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New one-step model of breast tumor locating based on deep learning.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Breast cancer has the highest cancer prevalence rate among the women worldwide. Early detection of breast cancer is crucial for successful treatment and reducing cancer mortality rate. However, tumor detection of breast ultrasound (US) im...
Algorithms Female Breast Neoplasms Deep Learning Image Processing, Computer-Assisted Mammography Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Ultrasonography, Mammary Breast
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Breast mass detection and diagnosis using fused features with density.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of...
Breast Neoplasms Databases, Factual Mammography Middle Aged Female Humans Radiographic Image Interpretation, Computer-Assisted Aged ROC Curve Breast Adult Unsupervised Machine Learning
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A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound: Added value for the inexperienced breast radiologist.

Medicine Jan 1, 2019
To evaluate the value of the computer-aided diagnosis (CAD) program applied to diagnostic breast ultrasonography (US) based on operator experience.US images of 100 breast masses from 91 women over 2 months (from May to June 2015) were collected and r...
Adolescent ROC Curve Follow-Up Studies Radiologists Middle Aged Diagnosis, Computer-Assisted Clinical Competence Ultrasonography, Mammary Breast Observer Variation Retrospective Studies Female Aged Young Adult Adult Sensitivity and Specificity Breast Neoplasms Humans Artificial Intelligence
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[Current applications of artificial intelligence in tumor histopathology].

Zhonghua zhong liu za zhi [Chinese journal of oncology] Dec 23, 2018
The tasks of artificial intelligence (AI) in tumor histopathology include image segmentation and classification. Currently, the specific contents including lymph node metastasis, pathological classification, grade and prognostic evaluation of maligna...
Sentinel Lymph Node Biopsy Breast Neoplasms Humans Frozen Sections Lymph Nodes Artificial Intelligence Lymphatic Metastasis Female Sentinel Lymph Node
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Morphology-based prediction of cancer cell migration using an artificial neural network and a random decision forest.

Integrative biology : quantitative biosciences from nano to macro Dec 19, 2018
Metastasis is the cause of death in most patients of breast cancer and other solid malignancies. Identification of cancer cells with highly migratory capability to metastasize relies on markers for epithelial-to-mesenchymal transition (EMT), a proces...
Neoplasm Metastasis Lab-On-A-Chip Devices Neural Networks, Computer Algorithms Cell Movement Decision Support Techniques Epithelial-Mesenchymal Transition Female Models, Biological Deep Learning Humans Cell Line, Tumor Single-Cell Analysis Mice Reproducibility of Results Breast Neoplasms Animals Neoplasms
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Application of Artificial Intelligence-based Technology in Cancer Management: A Commentary on the Deployment of Artificial Neural Networks.

Anticancer research Dec 1, 2018
Artificial intelligence was recognised many years ago as a potential and powerful tool to predict disease outcome in many clinical situations. The conventional approaches using statistical methods have provided much information, but are subject to li...
Humans Breast Neoplasms Fuzzy Logic Neural Networks, Computer Artificial Intelligence Prognosis Female
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