AIMC Topic: Carcinoma, Non-Small-Cell Lung

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Drug repositioning for non-small cell lung cancer by using machine learning algorithms and topological graph theory.

BMC bioinformatics Jan 11, 2016
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily over several years. Drug repositioning is the current trend in the pharmaceutical industry for ident...
Neoplasm Proteins Drug Repositioning Microarray Analysis Gene Expression Regulation, Neoplastic Signal Transduction Models, Theoretical Carcinoma, Non-Small-Cell Lung Humans Drug Discovery Machine Learning Antineoplastic Agents Lung Neoplasms Algorithms
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Machine Learning methods for Quantitative Radiomic Biomarkers.

Scientific reports Aug 17, 2015
Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care. In this radi...
Carcinoma, Non-Small-Cell Lung Area Under Curve Survival Analysis Machine Learning Tomography, X-Ray Computed Biomarkers, Tumor Humans ROC Curve Lung Neoplasms
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Cancer adjuvant chemotherapy strategic classification by artificial neural network with gene expression data: An example for non-small cell lung cancer.

Journal of biomedical informatics May 18, 2015
PURPOSE: Adjuvant chemotherapy (ACT) is used after surgery to prevent recurrence or metastases. However, ACT for non-small cell lung cancer (NSCLC) is still controversial. This study aimed to develop prediction models to distinguish who is suitable f...
Lung Neoplasms Humans Computational Biology Prognosis Neural Networks, Computer Carcinoma, Non-Small-Cell Lung Aged Machine Learning Gene Expression Regulation, Neoplastic Female Neoplasm Recurrence, Local Algorithms Kaplan-Meier Estimate Male Treatment Outcome Reproducibility of Results Neoplasm Metastasis Middle Aged Chemotherapy, Adjuvant Proportional Hazards Models Gene Expression Profiling
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Application of an artificial neural network model for selection of potential lung cancer biomarkers.

Journal of breath research May 6, 2015
Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In...
Case-Control Studies Humans Lung Neoplasms Neural Networks, Computer Adenocarcinoma Sensitivity and Specificity Female Aged Carcinoma, Non-Small-Cell Lung Biomarkers, Tumor Breath Tests Aged, 80 and over Volatile Organic Compounds Mass Spectrometry Male Exhalation Young Adult Smoking Middle Aged Gas Chromatography-Mass Spectrometry Small Cell Lung Carcinoma Adult Solid Phase Microextraction
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Lung cancer prediction using neural network ensemble with histogram of oriented gradient genomic features.

TheScientificWorldJournal Feb 23, 2015
This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their "nonensemble" variants for lung cancer prediction. These machine learning classifiers were trained to predict lung c...
ErbB Receptors Support Vector Machine Humans Proto-Oncogene Proteins p21(ras) Carcinoma, Non-Small-Cell Lung Neural Networks, Computer Mutation Biomarkers, Tumor Lung Neoplasms Tumor Suppressor Protein p53
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Application of machine learning to develop and validate a pain risk prediction model for patients with non-small cell lung cancer after video-assisted thoracoscopic surgery: A single-center retrospective study.

Medicine Jan 9, 2026
This study aimed to develop a machine learning (ML)-based model to identify risk factors for postoperative pain following video-assisted thoracoscopic surgery (VATS) lobectomy in non-small cell lung cancer (NSCLC) patients. This retrospective study a...
Humans Machine Learning Retrospective Studies Female Risk Factors ROC Curve Lung Neoplasms Aged Male Carcinoma, Non-Small-Cell Lung Middle Aged Risk Assessment Pain, Postoperative Thoracic Surgery, Video-Assisted
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Large-Scale T-cell Receptor Repertoire Profiling Unveils Tumor-Specific Signals for Diagnosing Indeterminate Pulmonary Nodules.

Cancer research Dec 15, 2025
UNLABELLED: Indeterminate pulmonary nodules (IPN) are increasingly detected due to increasing health awareness and widespread lung cancer screening, yet distinguishing benign from malignant nodules remains a critical challenge. Emerging evidence sugg...
Humans Receptors, Antigen, T-Cell Prospective Studies Carcinoma, Non-Small-Cell Lung Multiple Pulmonary Nodules Male Solitary Pulmonary Nodule Middle Aged Female Lung Neoplasms Aged
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[Comprehensive bioinformatics analysis and machine learning to investigate the regulatory mechanism and clinical value of secreted phosphoprotein 1 gene in lung squamous cell carcinoma].

Zhonghua yi xue za zhi Dec 2, 2025
This study aimed to comprehensively investigate the regulatory mechanism and clinical value of secreted phosphoprotein 1 (SPP1) in the three-stage progression of "smoking-chronic obstructive pulmonary disease (COPD)-carcinogenesis" in lung squamous ...
Humans Machine Learning Prognosis Carcinoma, Non-Small-Cell Lung Gene Regulatory Networks Osteopontin Lung Neoplasms Computational Biology Gene Expression Regulation, Neoplastic Carcinoma, Squamous Cell Pulmonary Disease, Chronic Obstructive Male Gene Expression Profiling
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Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Journal of medical economics Dec 1, 2025
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...
Quality-Adjusted Life Years Spain Early Detection of Cancer Decision Trees Cost-Benefit Analysis Markov Chains Machine Learning Tomography, X-Ray Computed Female Aged Risk Assessment Lung Neoplasms Carcinoma, Non-Small-Cell Lung Male Middle Aged Humans
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Decoding Dendritic Cell Subtypes via Integrated Radiogenomics: A Stacked Ensemble Model for Predicting Immunotherapy Response in NSCLC.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology Nov 15, 2025
We pioneer a multimodal framework integrating single-cell RNA sequencing (scRNA-seq), radiomics, and deep learning to decipher dendritic cell (DC)-mediated mechanisms underlying anti-PD-1 response in non-small cell lung cancer (NSCLC). Single-cell RN...
Humans Female Biomarkers, Tumor Gene Expression Regulation, Neoplastic Carcinoma, Non-Small-Cell Lung Dendritic Cells Single-Cell Analysis Lung Neoplasms Immunotherapy
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