AIMC Topic: Adenocarcinoma of Lung

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Predicting Gene Comutation of EGFR and TP53 by Radiomics and Deep Learning in Patients With Lung Adenocarcinomas.

Journal of thoracic imaging May 1, 2025
PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of epidermal growth factor receptor ( EGFR ) and TP53 mutations and to assess the models' capacities t...
Deep Learning Lung Neoplasms Mutation Tumor Suppressor Protein p53 ErbB Receptors Adenocarcinoma of Lung Radiomics Male Middle Aged Lung Reproducibility of Results Aged Humans Adult Retrospective Studies Sensitivity and Specificity Tomography, X-Ray Computed Female
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Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

Journal of translational medicine Apr 29, 2025
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...
Molecular Targeted Therapy ErbB Receptors Protein Kinase Inhibitors Adenocarcinoma of Lung Middle Aged Deep Learning Lung Neoplasms Mutation Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Male
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F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BMC medical imaging Apr 28, 2025
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
Humans Retrospective Studies Female Aged Male Adenocarcinoma of Lung Middle Aged Positron Emission Tomography Computed Tomography Deep Learning Neoplasm Grading Lung Neoplasms Radiopharmaceuticals Nomograms Fluorodeoxyglucose F18
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Habitat Radiomics and Deep Learning Features Based on CT for Predicting Lymphovascular Invasion in T1-stage Lung Adenocarcinoma: A Multicenter Study.

Academic radiology Apr 18, 2025
RATIONALE AND OBJECTIVES: The research aims to examine how CT-derived habitat radiomics can be used to predict lymphovascular invasion (LVI) in patients with T1-stage lung adenocarcinoma (LUAD), and compare its effectiveness to traditional radiomics ...
Neoplasm Invasiveness Tomography, X-Ray Computed Neoplasm Staging Humans Male Adenocarcinoma of Lung Female Middle Aged Retrospective Studies Deep Learning Aged Lung Neoplasms Radiomics Lymphatic Metastasis
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The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.

Frontiers in immunology Apr 17, 2025
OBJECTIVE: Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. This study aims to investigate the relationship between gene e...
Databases, Genetic Gene Regulatory Networks Mitophagy Humans Autophagy Lung Neoplasms Machine Learning Computational Biology Mitochondria Biomarkers, Tumor Gene Expression Regulation, Neoplastic Adenocarcinoma of Lung Gene Expression Profiling
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MLG2Net: Molecular Global Graph Network for Drug Response Prediction in Lung Cancer Cell Lines.

Journal of medical systems Apr 10, 2025
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines be...
Deep Learning Humans Pharmacogenetics Neural Networks, Computer Cell Line, Tumor Adenocarcinoma of Lung Precision Medicine Lung Neoplasms Antineoplastic Agents
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A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 3, 2025
Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early identification of malignant pulmonary nodules constitutes the most effective approach to reducing the mortality of LUAD. Despite the wide application o...
Multiple Pulmonary Nodules Antibodies, Monoclonal Iodine Radioisotopes Zirconium Cell Adhesion Molecules Cell Line, Tumor Lung Neoplasms Mice Antibodies, Monoclonal, Humanized Radioisotopes Adenocarcinoma of Lung Theranostic Nanomedicine Humans Female Animals
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Analysis of Multiple Programmed Cell Death Patterns and Functional Validations of Apoptosis-Associated Genes in Lung Adenocarcinoma.

Annals of surgical oncology Apr 2, 2025
BACKGROUND: Lung adenocarcinoma (LUAD) is marked by its considerable aggressiveness and pronounced heterogeneity. Programmed cell death (PCD) plays a pivotal role in the progression of tumors, their aggressive behavior, resistance to treatment, and r...
Machine Learning Prognosis Female Survival Rate Biomarkers, Tumor Gene Expression Regulation, Neoplastic Humans Male Follow-Up Studies Middle Aged Apoptosis Gene Expression Profiling Apoptosis Regulatory Proteins Lung Neoplasms Adenocarcinoma of Lung
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Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles.

Cancer biomarkers : section A of Disease markers Apr 2, 2025
ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance clinical decision-making accuracy.MethodsData from The Cancer Genome Atlas (TCGA) for LUAD patients...
Gene Expression Profiling ROC Curve Humans Lung Neoplasms Machine Learning Gene Expression Regulation, Neoplastic Early Detection of Cancer Aged Prognosis Nomograms MicroRNAs Female Biomarkers, Tumor Adenocarcinoma of Lung Male Middle Aged
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A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.

Medical physics Apr 1, 2025
BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potential for rapid metastasis and frequent recurrence. Therefore, accurately predicting the presence of high-grade components is crucial for doctors to devel...
Neural Networks, Computer Tomography, X-Ray Computed Female Aged Male Humans Neoplasm Staging Neoplasm Grading Adenocarcinoma of Lung Middle Aged Image Processing, Computer-Assisted Lung Neoplasms Neoplasm Invasiveness
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