AIMC Topic: ErbB Receptors

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GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Scientific reports Jan 25, 2024
Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a comb...
Isocitrate Dehydrogenase Cyclin-Dependent Kinase Inhibitor Proteins Adjuvants, Pharmaceutic Humans ErbB Receptors Adult Deep Learning Glioma DNA Copy Number Variations Adjuvants, Immunologic
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Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Jan 9, 2024
BACKGROUND: Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate EGFR genotyping is crucial for optimal treatment outcomes. Conventional methods for identifying the EGFR genotype have several limitations. Therefore, ...
Aged Adult Male Humans Tomography, X-Ray Computed Female Mutation ErbB Receptors Adenocarcinoma of Lung Middle Aged Deep Learning Lung Neoplasms
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Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

Scientific reports Jan 9, 2024
This study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients...
Radiomics Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Humans
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T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Journal of biomolecular structure & dynamics Jan 4, 2024
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug di...
Cell Line, Tumor Protein Binding Cell Proliferation Drug Resistance, Neoplasm Apoptosis ErbB Receptors Molecular Docking Simulation Drug Screening Assays, Antitumor Protein Kinase Inhibitors Drug Discovery Mutation Antineoplastic Agents Humans Machine Learning
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A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

European radiology experimental Jan 2, 2024
BACKGROUND: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epidermal growth factor receptor (EGFR), EGFR exon 19 deletion (19Del), and EGFR exon 21-point mutation...
Magnetic Resonance Imaging Humans Mutation Retrospective Studies ErbB Receptors Brain Neoplasms Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis.

Journal of translational medicine Nov 7, 2023
BACKGROUND: The precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial goals in computer-aided lung adenocarcinoma brain metastasis diagnosis. However, these two tasks prese...
Humans Lung Neoplasms Genotype Brain Neoplasms ErbB Receptors Deep Learning Image Processing, Computer-Assisted
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A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

Academic radiology Jul 21, 2023
RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and valid...
ErbB Receptors Humans Head and Neck Neoplasms Mutation Deep Learning Retrospective Studies Nomograms Tomography, X-Ray Computed Squamous Cell Carcinoma of Head and Neck Radiomics
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High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BMC pulmonary medicine Jul 5, 2023
BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer is critical for tyrosine kinase inhibitor therapy. EGFR detection requires tissue samples, which are difficult to obtain in som...
Lung Neoplasms Adenocarcinoma Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Humans Deep Learning
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Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

ACS sensors Jun 6, 2023
Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutate...
ErbB Receptors Protein Kinase Inhibitors Carcinoma, Non-Small-Cell Lung Mutation Exosomes Humans Deep Learning Lung Neoplasms Spectrum Analysis, Raman
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Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

Physical and engineering sciences in medicine Mar 1, 2023
The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate patient management and outcome improvement. However, the disease progression is influenced by multi...
Radiosurgery Brain Neoplasms ErbB Receptors Deep Learning Lung Neoplasms Humans Retrospective Studies
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