AIMC Topic: Adenocarcinoma of Lung

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A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

Acta radiologica (Stockholm, Sweden : 1987) Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Adult Radiomics Brain Neoplasms Male Brain Retrospective Studies Female Aged Feasibility Studies Image Interpretation, Computer-Assisted Adenocarcinoma of Lung Multiparametric Magnetic Resonance Imaging Middle Aged Deep Learning Lung Neoplasms Magnetic Resonance Imaging Humans
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Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.

Cancer science Nov 3, 2024
Viruses are widely recognized to be intricately associated with both solid and hematological malignancies in humans. The primary goal of this research is to elucidate the interplay of genes between SARS-CoV-2 infection and lung adenocarcinoma (LUAD),...
Humans Tumor Microenvironment Lung Neoplasms Biomarkers, Tumor Gene Expression Regulation, Neoplastic Machine Learning Gene Expression Profiling Adenocarcinoma of Lung COVID-19 Transcriptome Prognosis SARS-CoV-2
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Quantitative analysis of imaging characteristics in lung adenocarcinoma in situ using artificial intelligence.

Thoracic cancer Oct 30, 2024
BACKGROUND: With the rising incidence of pulmonary nodules (PNs), lung adenocarcinoma in situ (AIS) is a critical early stage of lung cancer, necessitating accurate diagnosis for early intervention. This study applies artificial intelligence (AI) for...
Humans Artificial Intelligence Tomography, X-Ray Computed Male Female Lung Neoplasms Middle Aged Aged Adenocarcinoma of Lung Adult Adenocarcinoma in Situ
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Comprehensive multi-omics analysis identifies chromatin regulator-related signatures and TFF1 as a therapeutic target in lung adenocarcinoma through a 429-combination machine learning approach.

Frontiers in immunology Oct 30, 2024
INTRODUCTION: Lung cancer is a leading cause of cancer-related deaths, with its incidence continuing to rise. Chromatin remodeling, a crucial process in gene expression regulation, plays a significant role in the development and progression of malign...
Chromatin Trefoil Factor-1 Lung Neoplasms Mice Tumor Microenvironment Cell Proliferation Humans Multiomics Biomarkers, Tumor Machine Learning Apoptosis Gene Expression Regulation, Neoplastic Animals Prognosis Xenograft Model Antitumor Assays Cell Line, Tumor Female Adenocarcinoma of Lung
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Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

Thoracic cancer Oct 1, 2024
BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype...
Preoperative Period Adenocarcinoma of Lung Male Middle Aged Humans Deep Learning Lung Neoplasms Prognosis Tomography, X-Ray Computed Retrospective Studies Female Aged
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A vision transformer-based deep transfer learning nomogram for predicting lymph node metastasis in lung adenocarcinoma.

Medical physics Sep 28, 2024
BACKGROUND: Lymph node metastasis (LNM) plays a crucial role in the management of lung cancer; however, the ability of chest computed tomography (CT) imaging to detect LNM status is limited.
Female Lymphatic Metastasis Aged Deep Learning Adenocarcinoma of Lung Male Humans Image Processing, Computer-Assisted Middle Aged Tomography, X-Ray Computed Lung Neoplasms Nomograms
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Development and validation of machine learning models for diagnosis and prognosis of lung adenocarcinoma, and immune infiltration analysis.

Scientific reports Sep 27, 2024
The aim of our study was to develop robust diagnostic and prognostic models for lung adenocarcinoma (LUAD) using machine learning (ML) techniques, focusing on early immune infiltration. Feature selection was performed on The Cancer Genome Atlas (TCGA...
Adenocarcinoma of Lung Lung Neoplasms Gene Expression Regulation, Neoplastic Support Vector Machine Lymphocytes, Tumor-Infiltrating Prognosis Biomarkers, Tumor Gene Expression Profiling Humans ROC Curve Machine Learning Algorithms
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Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma.

Immunologic research Sep 25, 2024
Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given...
Humans Machine Learning Prognosis Biomarkers, Tumor Male Middle Aged Female Aged Drug Resistance, Neoplasm Asparagine Antineoplastic Agents Adenocarcinoma of Lung Lung Neoplasms Multiomics Gene Expression Regulation, Neoplastic
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Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer Sep 19, 2024
INTRODUCTION: An increasing number of early-stage lung adenocarcinomas (LUAD) are detected as lung nodules. The radiological features related to LUAD progression warrant further investigation. Exploration is required to bridge the gap between radiomi...
Support Vector Machine Adenocarcinoma of Lung Prognosis Tomography, X-Ray Computed Female Humans Aged Middle Aged Radiomics Disease Progression Male Lung Neoplasms
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Predicting invasion in early-stage ground-glass opacity pulmonary adenocarcinoma: a radiomics-based machine learning approach.

BMC medical imaging Sep 13, 2024
BACKGROUND: To design a pulmonary ground-glass nodules (GGN) classification method based on computed tomography (CT) radiomics and machine learning for prediction of invasion in early-stage ground-glass opacity (GGO) pulmonary adenocarcinoma.
Sensitivity and Specificity Radiomics Male Middle Aged Lung Neoplasms Neoplasm Invasiveness Adenocarcinoma of Lung Retrospective Studies Tomography, X-Ray Computed Female Humans Aged Machine Learning
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