AIMC Topic: Receptors, Estrogen

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Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.

IEEE transactions on medical imaging Aug 7, 2019
Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnostics. Determination of the proportion of stained cells (labeling index) should be restricted on malignant epithelial cells, carefully avoiding tumor inf...
Humans Algorithms Female Immunohistochemistry Receptors, Estrogen Receptors, Progesterone Keratins Ki-67 Antigen Breast Neoplasms Biomarkers, Tumor Deep Learning Epithelial Cells Image Interpretation, Computer-Assisted
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Deep learning driven QSAR model for environmental toxicology: Effects of endocrine disrupting chemicals on human health.

Environmental pollution (Barking, Essex : 1987) Jul 6, 2019
Over 80,000 endocrine-disrupting chemicals (EDCs) are considered emerging contaminants (ECs), which are of great concern due to their effects on human health. Quantitative structure-activity relationship (QSAR) models are a promising alternative to i...
Sex Hormone-Binding Globulin Ecotoxicology Environmental Pollutants Quantitative Structure-Activity Relationship Endocrine Disruptors Receptors, Estrogen Humans Neural Networks, Computer Deep Learning Computational Biology
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Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer.

JAMA network open Jul 3, 2019
IMPORTANCE: Immunohistochemistry (IHC) is the most widely used assay for identification of molecular biomarkers. However, IHC is time consuming and costly, depends on tissue-handling protocols, and relies on pathologists' subjective interpretation. I...
Humans Artificial Intelligence Algorithms Immunohistochemistry Receptor, ErbB-2 Receptors, Estrogen British Columbia Tissue Array Analysis Biomarkers, Tumor Middle Aged ROC Curve Predictive Value of Tests Feasibility Studies Retrospective Studies Female Reproducibility of Results Breast Neoplasms
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Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records.

Scientific reports Jun 25, 2019
Electronic health records (EHR) represent a rich resource for conducting observational studies, supporting clinical trials, and more. However, much of the data contains unstructured text, presenting an obstacle to automated extraction. Natural langua...
Datasets as Topic Receptor, ErbB-2 Receptors, Estrogen Receptors, Progesterone Algorithms Electronic Health Records Female Breast Neoplasms Natural Language Processing Humans Machine Learning
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Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

BMC cancer Jun 21, 2019
BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical s...
Middle Aged Lymph Nodes Lymphatic Metastasis Axilla Area Under Curve Aged, 80 and over Young Adult Adult Breast Neoplasms Sentinel Lymph Node Biopsy Carcinoma, Lobular Tumor Burden Neovascularization, Pathologic Linear Models Receptors, Estrogen Humans Neural Networks, Computer Retrospective Studies Female Aged
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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...
Receptors, Estrogen Receptors, Progesterone Humans Machine Learning Female Genomics RNA, Messenger Triple Negative Breast Neoplasms DNA Methylation DNA Copy Number Variations Receptor, ErbB-2
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Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.

Breast cancer research : BCR Jan 25, 2019
BACKGROUND: BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other ...
Female Aged Adult Breast Neoplasms Middle Aged Epigenomics Support Vector Machine DNA Methylation DNA Copy Number Variations Humans Promoter Regions, Genetic Receptors, Estrogen Breast Receptors, Progesterone Survival Analysis BRCA1 Protein Datasets as Topic Homologous Recombination CpG Islands
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Machine learning models for predicting endocrine disruption potential of environmental chemicals.

Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews Jan 10, 2019
We introduce here ML4Tox, a framework offering Deep Learning and Support Vector Machine models to predict agonist, antagonist, and binding activities of chemical compounds, in this case for the estrogen receptor ligand-binding domain. The ML4Tox mode...
Environmental Pollutants Quantitative Structure-Activity Relationship Toxicity Tests Endocrine Disruptors Receptors, Estrogen Machine Learning Computer Simulation Protein Binding Support Vector Machine
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Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.

Molecular pharmaceutics Aug 28, 2018
Many chemicals that disrupt endocrine function have been linked to a variety of adverse biological outcomes. However, screening for endocrine disruption using in vitro or in vivo approaches is costly and time-consuming. Computational methods, e.g., q...
Protein Binding Support Vector Machine Bayes Theorem Receptors, Estrogen Humans Machine Learning Software Algorithms Animals
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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...
Middle Aged ROC Curve Antineoplastic Combined Chemotherapy Protocols Neoadjuvant Therapy Follow-Up Studies Adult Survival Rate Breast Neoplasms Biomarkers, Tumor Carcinoma, Ductal, Breast Receptors, Estrogen Chemotherapy, Adjuvant Carcinoma, Lobular Magnetic Resonance Imaging Neoplasm Invasiveness Axilla Humans Receptor, ErbB-2 Neural Networks, Computer Retrospective Studies Algorithms Female Prognosis Aged Aged, 80 and over Young Adult
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