AIMC Topic: Receptor, ErbB-2

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Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring.

IEEE transactions on medical imaging Mar 22, 2019
Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on invasive breast cancer is regarded as a significant predictive and prognostic marker. We propose a novel deep reinforcement learning (DRL)-based model that treats imm...
Deep Learning Breast Image Interpretation, Computer-Assisted Immunohistochemistry Receptor, ErbB-2 Humans Algorithms Female Breast Neoplasms Biomarkers, Tumor
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Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Genes Mar 7, 2019
It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets...
Triple Negative Breast Neoplasms DNA Methylation DNA Copy Number Variations Receptor, ErbB-2 Receptors, Estrogen Receptors, Progesterone Humans Machine Learning Female Genomics RNA, Messenger
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Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

Breast cancer research and treatment Oct 16, 2018
PURPOSE: To determine whether a multivariate machine learning-based model using computer-extracted features of pre-treatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict pathologic complete response (pCR) to neoadjuvant ...
Image Processing, Computer-Assisted Triple Negative Breast Neoplasms Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Female Feasibility Studies Neoadjuvant Therapy Aged Magnetic Resonance Imaging Receptor, ErbB-2 Humans Adult Neoplasm Staging Mastectomy, Segmental Machine Learning Middle Aged Breast Retrospective Studies ROC Curve
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Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm.

Breast cancer research and treatment Sep 7, 2018
PURPOSE: This study aimed to develop mathematical tools to predict the likelihood of recurrence after neoadjuvant chemotherapy (NAC) plus trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer.
Humans Breast Neoplasms Brain Neoplasms Middle Aged Models, Theoretical Disease-Free Survival Receptor, ErbB-2 Machine Learning Retrospective Studies Female Aged Adult Trastuzumab Chemotherapy, Adjuvant
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Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Journal of magnetic resonance imaging : JMRI Aug 21, 2018
BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to quantitatively predict outcomes in patients who meet the criteria of estrogen receptor positive / human epidermal growth factor receptor-2 negative (ER+/...
Neoplasm Recurrence, Local Receptor, ErbB-2 Carcinoma, Ductal, Breast Estrogen Receptor alpha Imaging, Three-Dimensional Image Processing, Computer-Assisted Treatment Outcome Magnetic Resonance Imaging Area Under Curve Neural Networks, Computer Algorithms Retrospective Studies Female Reproducibility of Results Aged Adult Breast Neoplasms Middle Aged ROC Curve Humans
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Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

Annals of surgical oncology Jul 5, 2018
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to b...
Carcinoma, Ductal, Breast Receptors, Estrogen Chemotherapy, Adjuvant Carcinoma, Lobular Follow-Up Studies Magnetic Resonance Imaging Neoplasm Invasiveness Axilla Receptor, ErbB-2 Aged Aged, 80 and over Neural Networks, Computer Young Adult Adult Algorithms ROC Curve Survival Rate Prognosis Antineoplastic Combined Chemotherapy Protocols Humans Breast Neoplasms Retrospective Studies Neoadjuvant Therapy Biomarkers, Tumor Female Middle Aged
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Optimal adjuvant endocrine treatment of ER+/HER2+ breast cancer patients by age at diagnosis: A population-based cohort study.

European journal of cancer (Oxford, England : 1990) Dec 21, 2017
BACKGROUND: Prior randomised controlled trials on adjuvant hormonal therapy included HER2 patients; however, a differential effect of aromatase inhibitors (AIs) versus tamoxifen (TAM) may have been missed in ER+/HER2+ patients that comprise 7-15% of ...
Receptor, ErbB-2 Proportional Hazards Models Middle Aged Humans Aromatase Inhibitors Cohort Studies Antineoplastic Agents, Hormonal Female Disease-Free Survival Chemotherapy, Adjuvant Kaplan-Meier Estimate Aged Netherlands Tamoxifen Receptors, Estrogen Adult Age of Onset Breast Neoplasms
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Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

Journal of magnetic resonance imaging : JMRI Oct 16, 2017
BACKGROUND: Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentiall...
Aged Adult Breast Neoplasms Middle Aged Image Processing, Computer-Assisted Support Vector Machine Breast Diffusion Motion Image Interpretation, Computer-Assisted Machine Learning Algorithms Prospective Studies Female Reproducibility of Results Receptor, ErbB-2 Humans Estrogen Receptor alpha Diffusion Magnetic Resonance Imaging Echo-Planar Imaging
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Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.

Scientific reports Apr 5, 2017
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligen...
Antineoplastic Agents, Immunological Immunohistochemistry Receptor, ErbB-2 Trastuzumab Female Humans Biomarkers, Tumor Reproducibility of Results Diagnosis, Computer-Assisted Machine Learning Breast Neoplasms Cohort Studies
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A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Feb 13, 2017
The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who require adjuvant chemotherapy in contrast to those that will respond to hormonal therapy. To distingu...
Image Interpretation, Computer-Assisted Receptor, ErbB-2 Histocytochemistry Humans Mitotic Index Risk Breast Neoplasms Female Eosine Yellowish-(YS) Mitosis Biomarkers, Tumor Hematoxylin Support Vector Machine Gene Expression Neoplasm Grading
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