AIMC Topic: ErbB Receptors

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Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction.

BMC bioinformatics Nov 12, 2020
BACKGROUND: Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential r...
Lapatinib Protein Interaction Maps Afatinib Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation MAP Kinase Signaling System Quantitative Structure-Activity Relationship ErbB Receptors Protein Kinase Inhibitors Humans Neural Networks, Computer Precision Medicine Cell Line, Tumor
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Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research Nov 4, 2020
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...
Algorithms Tomography, X-Ray Computed Female Reproducibility of Results Humans Machine Learning Carcinoma, Non-Small-Cell Lung Male Area Under Curve ROC Curve Mutation Lung Neoplasms ErbB Receptors Adenocarcinoma
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Non-invasive decision support for NSCLC treatment using PET/CT radiomics.

Nature communications Oct 16, 2020
Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during...
Humans Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Positron Emission Tomography Computed Tomography Female Aged Male Middle Aged Mutation Progression-Free Survival ErbB Receptors Protein Kinase Inhibitors
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Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.

Journal of chemical information and modeling Sep 23, 2020
Kinase inhibitors are widely used in antitumor research, but there are still many problems such as drug resistance and off-target toxicity. A more suitable solution is to design a multitarget inhibitor with certain selectivity. Herein, computational ...
Support Vector Machine Quantitative Structure-Activity Relationship ErbB Receptors Machine Learning Molecular Docking Simulation
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Using machine learning to improve ensemble docking for drug discovery.

Proteins May 25, 2020
Ensemble docking has provided an inexpensive method to account for receptor flexibility in molecular docking for virtual screening. Unfortunately, as there is no rigorous theory to connect the docking scores from multiple structures to measured activ...
Drug Discovery User-Computer Interface Protein Binding Support Vector Machine Binding Sites Bayes Theorem Protein Structure, Secondary Ligands ErbB Receptors Humans Protein Kinase Inhibitors Molecular Docking Simulation
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Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Feb 17, 2020
BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor ...
ErbB Receptors Mutation Imaging Genomics Aged Radiopharmaceuticals Sensitivity and Specificity Image Interpretation, Computer-Assisted Machine Learning Male Fluorodeoxyglucose F18 Humans Retrospective Studies Lung Lung Neoplasms Female Carcinoma, Non-Small-Cell Lung Reproducibility of Results Predictive Value of Tests Positron Emission Tomography Computed Tomography
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Predictive models for patients with lung carcinomas to identify EGFR mutation status via an artificial neural network based on multiple clinical information.

Journal of cancer research and clinical oncology Dec 5, 2019
PURPOSE: Epidermal growth factor receptor (EGFR) mutation testing has several limitations. Therefore, we built predictive models to determine the EGFR mutation status of patients and guide therapeutic decision-making.
Humans Neural Networks, Computer Female Aged Male Middle Aged Lung Neoplasms Mutation ErbB Receptors Decision Making, Computer-Assisted
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Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.

Scientific reports Nov 28, 2019
Radiogenomics investigates the relationship between imaging phenotypes and genetic expression. Breast cancer is a heterogeneous disease that manifests complex genetic changes and various prognosis and treatment response. We investigate the value of m...
Ki-67 Antigen Neoplasm Invasiveness Neoplasm Grading ErbB Receptors Receptors, Estrogen Aged, 80 and over Machine Learning Adult Tomography, X-Ray Computed Humans Breast Neoplasms Female Middle Aged Aged
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Cross-registry neural domain adaptation to extract mutational test results from pathology reports.

Journal of biomedical informatics Aug 8, 2019
OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs), to extract mutational test results from pathology reports collected by cancer registries. Given the lack of hand-labeled datasets for mutational te...
Lung Neoplasms Computational Biology Neural Networks, Computer Carcinoma, Non-Small-Cell Lung Registries Humans Machine Learning Mutation Data Mining Neoplasms ErbB Receptors Deep Learning
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Recognition of early and late stages of bladder cancer using metabolites and machine learning.

Metabolomics : Official journal of the Metabolomic Society Jun 20, 2019
INTRODUCTION: Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and ...
Area Under Curve Neoplasm Staging Insulin Amino Acids ROC Curve Glycine Humans Proto-Oncogene Proteins c-akt Urinary Bladder Neoplasms Machine Learning Metabolic Networks and Pathways Galactose Software ErbB Receptors Biomarkers, Tumor
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