AIMC Topic: Adenocarcinoma of Lung

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Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

Aging Dec 9, 2020
The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cance...
Prognosis Female Aged Tumor Microenvironment Biomarkers, Tumor Humans Gene Ontology Adenocarcinoma of Lung Receptors, CCR4 Receptors, Purinergic P2 Receptors, Purinergic P2Y12 Male Middle Aged Lung Neoplasms Gene Expression Regulation, Neoplastic Receptors, CCR2
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Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BMC genomics Sep 22, 2020
BACKGROUND: The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far ...
Cluster Analysis Supervised Machine Learning Adenocarcinoma of Lung Humans Software Biomarkers, Tumor Lung Neoplasms Genomics
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A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.

Computational and mathematical methods in medicine Aug 1, 2020
BACKGROUND: The differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonar...
Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Deep Learning Expert Systems Humans Lung Neoplasms Expert Testimony Adenocarcinoma of Lung Artificial Intelligence Carcinoma, Non-Small-Cell Lung Databases, Factual Multiple Pulmonary Nodules Tomography, X-Ray Computed Solitary Pulmonary Nodule
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Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.

Nature communications Jul 16, 2020
Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address...
Lung Neoplasms Humans Early Detection of Cancer Machine Learning Metabolomics Sensitivity and Specificity Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Biomarkers, Tumor Adenocarcinoma of Lung
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Middle Aged Diagnosis, Computer-Assisted Deep Learning ROC Curve Image Processing, Computer-Assisted Tomography, X-Ray Computed Female Adult Male Regression Analysis Diagnosis, Differential Granuloma Tuberculosis Sex Factors Lung Neoplasms Logistic Models Nomograms Age Factors Solitary Pulmonary Nodule Humans Algorithms Retrospective Studies Adenocarcinoma of Lung Diagnostic Tests, Routine Observer Variation Pattern Recognition, Automated Calibration
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Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.

European journal of radiology Jun 25, 2020
PURPOSE: Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the ...
Lung Deep Learning Lung Neoplasms Diagnosis, Differential Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Adenocarcinoma of Lung Tomography, X-Ray Computed Female Reproducibility of Results Male Middle Aged Humans Prognosis
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Humans Machine Learning Carcinoma, Squamous Cell Gene Expression Profiling Transcriptome Lung Neoplasms Membrane Transport Proteins Monte Carlo Method Serpins Adenocarcinoma of Lung Cystatin A Cadherins Computational Biology Datasets as Topic Gene Expression Regulation, Neoplastic Tumor Suppressor Proteins Transcription Factors Adenosine Triphosphatases Diagnosis, Differential Terminology as Topic
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A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

Lung cancer (Amsterdam, Netherlands) Apr 25, 2020
OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the ...
Lymphatic Metastasis Adenocarcinoma of Lung Humans Tomography, X-Ray Computed Deep Learning Lung Neoplasms Lymph Nodes
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Real world study for the concordance between IBM Watson for Oncology and clinical practice in advanced non-small cell lung cancer patients at a lung cancer center in China.

Thoracic cancer Mar 19, 2020
BACKGROUND: IBM Watson for Oncology (WFO) provides physicians with evidence-based treatment options. This study was designed to explore the concordance of the suggested therapeutic regimen for advanced non-small cell lung (NSCLC) cancer patients betw...
Patient Selection Practice Guidelines as Topic Evidence-Based Medicine Adenocarcinoma of Lung Decision Support Systems, Clinical Lung Neoplasms United States Carcinoma, Non-Small-Cell Lung Follow-Up Studies Survival Rate Male Middle Aged China Prognosis Retrospective Studies Humans Clinical Decision-Making Artificial Intelligence Female Carcinoma, Squamous Cell
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CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

European radiology Feb 28, 2020
PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography ...
Middle Aged ROC Curve Image Processing, Computer-Assisted Humans Lung Neoplasms Neoplasm Invasiveness Female Machine Learning Logistic Models Neoplasm Recurrence, Local Risk Factors Retrospective Studies Adenocarcinoma of Lung Sensitivity and Specificity Tomography, X-Ray Computed Male
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