AIMC Topic: ErbB Receptors

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Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Medical physics Nov 7, 2021
PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.
Lung Neoplasms Mutation ErbB Receptors Adenocarcinoma of Lung Humans Retrospective Studies Deep Learning
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Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences Aug 26, 2021
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...
Neoplasm Staging Mutation Supervised Machine Learning ErbB Receptors Biomarkers ROC Curve Tomography, X-Ray Computed Proto-Oncogene Proteins p21(ras) Lung Neoplasms Female Humans Carcinoma, Non-Small-Cell Lung Aged Reproducibility of Results Machine Learning Aged, 80 and over Algorithms Male Middle Aged
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Digital/Computational Technology for Molecular Cytology Testing: A Short Technical Note with Literature Review.

Acta cytologica Apr 30, 2021
This short article describes the method of digital cytopathology using Z-stack scanning with or without extended focusing. This technology is suitable to observe such thick clusters as adenocarcinoma on cytologic specimens. Artificial intelligence (A...
Molecular Diagnostic Techniques Predictive Value of Tests Mutation DNA Mutational Analysis Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Lung Neoplasms ErbB Receptors Adenocarcinoma of Lung Pathology, Molecular Humans Artificial Intelligence Automation, Laboratory Reproducibility of Results
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Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in Wild-Type Metastatic Colorectal Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 22, 2021
PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastatic colorectal cancer (mCRC). However, ligand RNA assays have not been adopted into routine practice ...
Artificial Intelligence Colorectal Neoplasms Antineoplastic Combined Chemotherapy Protocols ErbB Receptors Humans Panitumumab Proto-Oncogene Proteins p21(ras) Amphiregulin Epiregulin
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Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.

JAMA network open Dec 1, 2020
IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant-positive non-small cell lung cancer (...
Proportional Hazards Models ErbB Receptors Protein Kinase Inhibitors Predictive Value of Tests Humans Antineoplastic Protocols Neoplasm Staging Machine Learning Antineoplastic Agents Mutation Prognosis Lung Neoplasms Survival Analysis Female Carcinoma, Non-Small-Cell Lung Male Middle Aged
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Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning.

Nature communications Nov 17, 2020
Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we u...
Neural Networks, Computer Algorithms Databases, Factual Deep Learning Microscopy, Fluorescence Fluorescence Resonance Energy Transfer ErbB Receptors Single Molecule Imaging
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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...
Protein Kinase Inhibitors Lapatinib Afatinib Mutation MAP Kinase Signaling System Quantitative Structure-Activity Relationship ErbB Receptors Humans Protein Interaction Maps Neural Networks, Computer Lung Neoplasms Precision Medicine Carcinoma, Non-Small-Cell Lung 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...
Mutation ErbB Receptors Humans Lung Neoplasms Adenocarcinoma Machine Learning Reproducibility of Results Carcinoma, Non-Small-Cell Lung Algorithms Male Area Under Curve Tomography, X-Ray Computed ROC Curve Female
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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...
Aged Progression-Free Survival Lung Neoplasms Humans Male ErbB Receptors Female Carcinoma, Non-Small-Cell Lung Middle Aged Protein Kinase Inhibitors Positron Emission Tomography Computed Tomography Deep Learning Mutation
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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 ...
Quantitative Structure-Activity Relationship Machine Learning ErbB Receptors Molecular Docking Simulation Support Vector Machine
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