Lung Cancer

How artificial intelligence is transforming lung cancer detection, diagnosis, and treatment.

518 Papers Open Access

Showing all 518 papers

Cited by 771
Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

Clin Cancer Res, 2019

Open Access
Cited by 318
Deep learning classification of lung cancer histology using CT images

Sci Rep, 2021

Open Access
Cited by 305
Machine Learning for Lung Cancer Diagnosis Treatment and Prognosis

Genomics Proteomics Bioinformatics, 2022

Open Access
Cited by 205
A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images

Diagnostics (Basel), 2023

Open Access
Cited by 168
Advances in molecular pathology and therapy of non-small cell lung cancer

Signal Transduct Target Ther, 2025

Open Access
Cited by 168
Artificial Intelligence in Lung Cancer Screening: The Future Is Now

Cancers (Basel), 2023

Open Access
Cited by 162
Artificial Intelligence and Lung Cancer: Impact on Improving Patient Outcomes

Cancers (Basel), 2023

Open Access
Cited by 150
Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine

Cold Spring Harb Perspect Med, 2021

Open Access
Cited by 136
Histopathology images-based deep learning prediction of prognosis and therapeutic response in small cell lung cancer

NPJ Digit Med, 2024

Open Access
Cited by 106
Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?

Transl Lung Cancer Res, 2021

Open Access
Cited by 103
Integration of artificial intelligence in lung cancer: Rise of the machine

Cell Rep Med, 2023

Open Access
Cited by 98
Artificial Intelligence and its future potential in lung cancer screening

EXCLI J, 2020

Open Access
Cited by 92
Deep Learning for Lung Cancer Diagnosis, Prognosis and Prediction Using Histological and Cytological Images: A Systematic Review

Cancers (Basel), 2023

Open Access
Cited by 83
Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection

Nat Med, 2025

Open Access
Cited by 77
A physics-guided modular deep-learning based automated framework for tumor segmentation in PET

Phys Med Biol, 2020

Open Access
Cited by 73
Tumour and microenvironment crosstalk in NSCLC progression and response to therapy

Nat Rev Clin Oncol, 2025

Open Access
Cited by 68
Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation

Sci Rep, 2025

Open Access
Cited by 62
Mitochondrial Pathway Signature (MitoPS) predicts immunotherapy response and reveals NDUFB10 as a key immune regulator in lung adenocarcinoma

J Immunother Cancer, 2025

Open Access
Cited by 52
Co-expression network analysis identified KIF2C in association with progression and prognosis in lung adenocarcinoma

Cancer Biomark, 2019

Open Access
Cited by 46
Progress and challenges of artificial intelligence in lung cancer clinical translation

NPJ Precis Oncol, 2025

Open Access
Cited by 41
Assessments of lung nodules by an artificial intelligence chatbot using longitudinal CT images

Cell Rep Med, 2025

Open Access
Cited by 40
Spatial signatures for predicting immunotherapy outcomes using multi-omics in non-small cell lung cancer

Nat Genet, 2025

Open Access
Cited by 39
Deep learning-based automatic segmentation of cardiac substructures for lung cancers

Radiother Oncol, 2024

Open Access
Cited by 36
Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes

ACS Sens, 2025

Open Access
Cited by 35
AI-enabled virtual spatial proteomics from histopathology for interpretable biomarker discovery in lung cancer

Nat Med, 2026

Open Access
Cited by 35
Deep learning-based lung cancer classification of CT images

BMC Cancer, 2025

Open Access
Cited by 34
Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis

Cancer Biomark, 2019

Open Access
Cited by 30
Advances in artificial intelligence applications in the field of lung cancer

Front Oncol, 2024

Open Access
Cited by 30
China Protocol for early screening, precise diagnosis, and individualized treatment of lung cancer

Signal Transduct Target Ther, 2025

Open Access
Cited by 25
Emerging molecular testing paradigms in non-small cell lung cancer management—current perspectives and recommendations

Oncologist, 2025

Open Access
Cited by 23
Developing an Innovative Lung Cancer Detection Model for Accurate Diagnosis in AI Healthcare Systems

Sci Rep, 2025

Open Access
Cited by 23
FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images

Sci Rep, 2025

Open Access
Cited by 22
Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy

J Transl Med, 2025

Open Access
Cited by 22
Lung cancer screening with low-dose CT: definition of positive, indeterminate, and negative screen results. A nodule management recommendation from the European Society of Thoracic Imaging

Eur Radiol, 2026

Open Access
Cited by 21
AI-enabled molecular phenotyping and prognostic predictions in lung cancer through multimodal clinical information integration

Cell Rep Med, 2025

Open Access
Cited by 21
Recent advances in biomarkers for predicting the efficacy of immunotherapy in non-small cell lung cancer

Front Immunol, 2025

Open Access
Cited by 20
A Systematic Review of AI Performance in Lung Cancer Detection on CT Thorax

Healthcare (Basel), 2025

Open Access
Cited by 20
Early detection of lung cancers – Comparison of computed tomography, cytology and fuzzy-based tumor markers panels

Cancer Biomark, 2009

Open Access
Cited by 20
Effectiveness of Artificial Intelligence Models in Predicting Lung Cancer Recurrence: A Gene Biomarker-Driven Review

Cancers (Basel), 2025

Open Access
Cited by 20
Landscape of 2D Deep Learning Segmentation Networks Applied to CT Scan from Lung Cancer Patients: A Systematic Review

J Imaging Inform Med, 2025

Open Access
Cited by 20
SVMVGGNet-16: A Novel Machine and Deep Learning Based Approaches for Lung Cancer Detection using Combined SVM and VGGNet-16

Curr Med Imaging, 2025

Open Access
Cited by 20
The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment

Int J Mol Sci, 2025

Open Access
Cited by 19
Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging

PLoS One, 2025

Open Access
Cited by 19
Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences

Med Phys, 2025

Open Access
Cited by 18
ESR Essentials: lung cancer screening with low-dose CT—practice recommendations by the European Society of Thoracic Imaging

Eur Radiol, 2026

Open Access
Cited by 17
A Comprehensive Review on the Application of Artificial Intelligence for Predicting Postsurgical Recurrence Risk in Early-Stage Non-Small Cell Lung Cancer Using Computed Tomography, Positron Emission Tomography, and Clinical Data

J Med Radiat Sci, 2025

Open Access
Cited by 17
Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules

Sci Rep, 2025

Open Access
Cited by 17
Hidden forces: the impact of cancer-associated fibroblasts on non-small cell lung cancer development and therapy

J Transl Med, 2025

Open Access
Cited by 17
Lung nodule detection using a multi-scale convolutional neural network and global channel spatial attention mechanisms

Sci Rep, 2025

Open Access
Cited by 16
MicroRNA-21: A potential therapeutic target in lung cancer (Review)

Int J Oncol, 2025

Open Access
Cited by 15
Cost-effective shallow genome-wide sequencing for profiling plasma cfDNA signatures to enhance lung cancer detection

Future Oncol, 2025

Open Access
Cited by 15
Deep learning-based histomorphological subtyping and risk stratification of small cell lung cancer from hematoxylin and eosin-stained whole slide images

Genome Med, 2025

Open Access
Cited by 15
The Current Roadmap of Lung Cancer Biology, Genomics and Racial Disparity

Int J Mol Sci, 2025

Open Access
Cited by 14
Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms

J Clin Pathol, 2025

Open Access
Cited by 14
Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer

BMC Med Imaging, 2025

Open Access
Cited by 14
Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

Front Public Health, 2025

Open Access
Cited by 14
Integrating circulating tumor DNA analysis and radiomics for dynamic risk assessment in localized lung cancer

Cancer Discov, 2025

Open Access
Cited by 14
Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT radiomic subtypes: a multi-cohort study

Int J Surg, 2025

Open Access
Cited by 14
Refining treatment strategies for non-small cell lung cancer lacking actionable mutations: insights from multi-omics studies

Br J Cancer, 2025

Open Access
Cited by 14
The Role of Plant-Derived Natural Products as a Regulator of the Tyrosine Kinase Pathway in the Management of Lung Cancer

Curr Issues Mol Biol, 2025

Open Access
Cited by 13
Integrated molecular and clinical characterization of pulmonary large cell neuroendocrine carcinoma

Nat Commun, 2025

Open Access
Cited by 13
M-GNN: A Graph Neural Network Framework for Lung Cancer Detection Using Metabolomics and Heterogeneous Graph Modeling

Int J Mol Sci, 2025

Open Access
Cited by 13
Malignancy risk stratification for pulmonary nodules: comparing a deep learning approach to multiparametric statistical models in different disease groups

Eur Radiol, 2025

Open Access
Cited by 12
AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer

Nat Commun, 2025

Open Access
Cited by 12
Identification of a Biomarker Panel in Extracellular Vesicles Derived From Non-Small Cell Lung Cancer (NSCLC) Through Proteomic Analysis and Machine Learning

J Extracell Vesicles, 2025

Open Access
Cited by 12
Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study

Ann Med, 2025

Open Access
Cited by 12
XLLC-Net: A lightweight and explainable CNN for accurate lung cancer classification using histopathological images

PLoS One, 2025

Open Access
Cited by 11
A lung CT vision foundation model facilitating disease diagnosis and medical imaging

Nat Commun, 2025

Open Access
Cited by 11
AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis

Sci Rep, 2025

Open Access
Cited by 11
Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Presenting as Part-Solid Nodules: A Multicenter Retrospective Study

Technol Cancer Res Treat, 2025

Open Access
Cited by 11
Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies

J Transl Med, 2025

Open Access
Cited by 11
Improving lung cancer detection with enhanced convolutional sequential networks

Sci Rep, 2025

Open Access
Cited by 11
Prediction of Malignancy and Pathological Types of Solid Lung Nodules on CT Scans Using a Volumetric SWIN Transformer

J Imaging Inform Med, 2025

Open Access
Cited by 11
Prediction of oncogene mutation status in non-small cell lung cancer: a systematic review and meta-analysis with a special focus on artificial intelligence-based methods

Eur Radiol, 2026

Open Access
Cited by 11
Protein biomarkers in lung cancer screening: technical considerations and feasibility assessment

Arch Bronconeumol, 2024

Open Access
Cited by 11
Redefining the Diagnostic and Therapeutic Landscape of Non-Small Cell Lung Cancer in the Era of Precision Medicine

J Clin Med, 2025

Open Access
Cited by 11
Segmentation-Guided Hybrid Deep Learning for Pulmonary Nodule Detection and Risk Prediction from Multi-Cohort CT Images

Diseases, 2026

Open Access
Cited by 11
The Development and Performance of Alternative Criteria for Lung Cancer Screening

Ann Intern Med, 2024

Open Access
Cited by 11
The landscape of conventional and artificial intelligence-based clinical prediction models in non-small-cell lung cancer: from development to real-world validation

ESMO Open, 2025

Open Access
Cited by 10
Decision level scheme for fusing multiomics and histology slide images using deep neural network for tumor prognosis prediction

Sci Rep, 2025

Open Access
Cited by 10
Deep Learning Based on Computed Tomography Predicts Response to Chemoimmunotherapy in Lung Squamous Cell Carcinoma

Aging Dis, 2024

Open Access
Cited by 10
Deep learning-based lung cancer risk assessment using chest computed tomography images without pulmonary nodules ≥8 mm

Transl Lung Cancer Res, 2025

Open Access
Cited by 10
Habitat-based radiomics from contrast-enhanced CT and clinical data to predict lymph node metastasis in clinical N0 peripheral lung adenocarcinoma ≤ 3 cm

Sci Rep, 2025

Open Access
Cited by 10
Innovative technologies and their clinical prospects for early lung cancer screening

Clin Exp Med, 2025

Open Access
Cited by 10
Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer

Sci Rep, 2025

Open Access
Cited by 10
Physiologically Based Pharmacokinetic Model of Tyrosine Kinase Inhibitors to Predict Target Site Penetration, with PET-Guided Verification

CPT Pharmacometrics Syst Pharmacol, 2025

Open Access
Cited by 10
Risk scoring model for lung adenocarcinoma based on PD-L1 related signature reveals prognostic predictability and correlation with tumor immune microenvironment genes

Front Immunol, 2025

Open Access
Cited by 10
The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC

Biomolecules, 2025

Open Access
Cited by 9
Deep Learning-Driven Multimodal Integration of miRNA and Radiomic for Lung Cancer Diagnosis

Biosensors (Basel), 2025

Open Access
Cited by 9
Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study

Sci Rep, 2025

Open Access
Cited by 9
Electronic-Nose Technology for Lung Cancer Detection: A Non-Invasive Diagnostic Revolution

Lung, 2025

Open Access
Cited by 9
Genomic and Immune Landscape Comparison of MET Exon 14 Skipping and MET-Amplified Non-Small Cell Lung Cancer

Clin Lung Cancer, 2024

Open Access
Cited by 9
Liquid biopsy using plasma proteomics in predicting efficacy and tolerance of PD-1/PD-L1 blockades in NSCLC: a prospective exploratory study

Mol Biomed, 2025

Open Access
Cited by 9
Machine Learning Model Integrating CT Radiomics of the Lung to Predict Checkpoint Inhibitor Pneumonitis in Patients with Advanced Cancer

Technol Cancer Res Treat, 2025

Open Access
Cited by 9
Pretreatment CT Texture Analysis for Predicting Survival Outcomes in Advanced Nonsmall Cell Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis

Thorac Cancer, 2025

Open Access
Cited by 9
Rapid and Noninvasive Early Detection of Lung Cancer by Integration of Machine Learning and Salivary Metabolic Fingerprints Using MS LOC Platform: A Large-Scale Multicenter Study

Adv Sci (Weinh), 2025

Open Access
Cited by 8
A prognostic PET radiomic model for risk stratification in non-small cell lung cancer: integrating radiogenomics and clinical features to predict survival and uncover tumor biology insights

J Cancer Res Clin Oncol, 2025

Open Access
Cited by 8
Application of a pulmonary nodule detection program using AI technology to ultra-low-dose CT: differences in detection ability among various image reconstruction methods

Jpn J Radiol, 2025

Open Access
Cited by 8
Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer

Cancer, 2025

Open Access
Cited by 8
Breakthroughs in immune checkpoint therapy: overcoming NSCLC immune checkpoint therapy resistance with novel techniques

Front Immunol, 2025

Open Access
Cited by 8
Classification of lung cancer severity using gene expression data based on deep learning

BMC Med Inform Decis Mak, 2025

Open Access
Cited by 8
Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT

BMC Med Imaging, 2025

Open Access
Cited by 8
Determination of lung cancer exhaled breath biomarkers using machine learning - a new analysis framework

Sci Rep, 2025

Open Access
Cited by 8
Development of a multi-neoepitope vaccine targeting non-small cell lung cancer through reverse vaccinology and bioinformatics approaches

Front Immunol, 2025

Open Access
Cited by 8
Diagnostic accuracy of AI in chest radiography for pneumonia and lung cancer: A meta-analysis

Eur J Radiol Open, 2025

Open Access
Cited by 8
Dose prediction via deep learning to enhance treatment planning of lung radiotherapy including simultaneous integrated boost techniques

Med Phys, 2025

Open Access
Cited by 8
Harnessing delta-like ligand 3: bridging biomarker discovery to next-generation immunotherapies in refractory small cell lung cancer

Front Immunol, 2025

Open Access
Cited by 8
Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis

Sci Rep, 2025

Open Access
Cited by 8
Image-based inference of tumor cell trajectories enables large-scale cancer progression analysis

Sci Adv, 2025

Open Access
Cited by 8
Integrative Analysis of Lung Adenocarcinoma Across Diverse Ethnicities and Exposures

Cancer Cell, 2025

Open Access
Cited by 8
Metabolic alterations driven by LDHA in CD8+ T cells promote immune evasion and therapy resistance in NSCLC

Sci Rep, 2025

Open Access
Cited by 8
Molecular advances in early-stage and locally advanced non-small cell lung carcinoma: Shaping the future of precision oncology - systematic review

Sci Prog, 2025

Open Access
Cited by 8
Predictive value of machine learning for radiation pneumonitis and checkpoint inhibitor pneumonitis in lung cancer patients: a systematic review and meta-analysis

Sci Rep, 2025

Open Access
Cited by 8
Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set

Sci Rep, 2025

Open Access
Cited by 8
Tumor aware recurrent inter-patient deformable image registration of computed tomography scans with lung cancer

Med Phys, 2025

Open Access
Cited by 7
2.5D deep learning radiomics and clinical data for predicting occult lymph node metastasis in lung adenocarcinoma

BMC Med Imaging, 2025

Open Access
Cited by 7
A weakly supervised deep learning framework for automated PD-L1 expression analysis in lung cancer

Front Immunol, 2025

Open Access
Cited by 7
Applications of artificial intelligence in non–small cell lung cancer: from precision diagnosis to personalized prognosis and therapy

J Transl Med, 2025

Open Access
Cited by 7
Artificial intelligence-based pulmonary vessel segmentation: an opportunity for automated three-dimensional planning of lung segmentectomy

Interdiscip Cardiovasc Thorac Surg, 2025

Open Access
Cited by 7
Enriched lung cancer classification approach using an optimized hybrid deep learning approach

Sci Rep, 2025

Open Access
Cited by 7
Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography

BMC Pulm Med, 2025

Open Access
Cited by 7
Meta-Learning on Augmented Gene Expression Profiles for Enhanced Lung Cancer Detection

AMIA Annu Symp Proc, 2024

Open Access
Cited by 7
Predicting PD-L1 expression status in NSCLC using radiomic analysis of 18F-FDG-PET/CT images

Eur J Nucl Med Mol Imaging, 2026

Open Access
Cited by 7
Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks

BMC Cancer, 2025

Open Access
Cited by 7
Pros and cons of reporting incidental findings in lung cancer screening

Eur Radiol, 2025

Open Access
Cited by 7
Secure and interpretable lung cancer prediction model using mapreduce private blockchain federated learning and XAI

Sci Rep, 2025

Open Access
Cited by 7
Thoracic CT radiomics analysis for predicting synchronous brain metastasis in patients with lung cancer

Diagn Interv Radiol, 2022

Open Access
Cited by 7
Time to Benefit for Lung Cancer Screening: A Systematic Review and Survival Meta-Analysis

Am J Prev Med, 2025

Open Access
Cited by 7
Utilizing Clinicopathological and Radiomic Features for Risk Stratification of Lung Cancer Recurrence

Acad Radiol, 2025

Open Access
Cited by 6
A multi-view CNN model to predict resolving of new lung nodules on follow-up low-dose chest CT

Insights Imaging, 2025

Open Access
Cited by 6
Artificial Intelligence and Machine Learning in Lung Cancer: Advances in Imaging, Detection, and Prognosis

Cancers (Basel), 2025

Open Access
Cited by 6
Deep Learning Predicts EGFR Mutation Status from Histology Images in Non-Small Cell Lung Cancer

Cancer Res Commun, 2025

Open Access
Cited by 6
DeepTFtyper: an interpretable morphology-aware graph neural network for translating histopathology images into molecular subtypes in small cell lung cancer

Brief Bioinform, 2025

Open Access
Cited by 6
DNA methyltransferase 3A (DNMT3A) mutations and PD-(L)1 blockade efficacy in non-small-cell lung cancer

Ann Oncol, 2025

Open Access
Cited by 6
Employment of artificial intelligence for early lung cancer diagnosis: a retrospective cohort study

BMJ Open Respir Res, 2025

Open Access
Cited by 6
Hypermetabolic pulmonary lesions detection and diagnosis based on PET/CT imaging and deep learning models

Eur J Nucl Med Mol Imaging, 2025

Open Access
Cited by 6
Integrating deep learning and multi-omics features in radiation pneumonitis prediction for lung cancer patients using PET/CT

BMC Med Imaging, 2025

Open Access
Cited by 6
Integrating peritumor and tumor CT radiomics features in predicting local control after SBRT in patients with pulmonary oligometastases

Radiat Oncol, 2025

Open Access
Cited by 6
Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma

Front Immunol, 2025

Open Access
Cited by 6
Multichannel deep learning prediction of major pathological response after neoadjuvant immunochemotherapy in lung cancer: a multicenter diagnostic study

Int J Surg, 2025

Open Access
Cited by 6
Multimodal omics analysis of the EGFR signaling pathway in non-small cell lung cancer and emerging therapeutic strategies

Oncol Res, 2025

Open Access
Cited by 6
Narrative review of the application of artificial intelligence-related technologies in the diagnosis of pulmonary nodules with recommendations for clinical practice and future research

J Thorac Dis, 2025

Open Access
Cited by 6
Noninvasive Prediction of Programmed Cell Death Protein-Ligand 1 Expression in Locally Advanced Non-small Cell Lung Cancer by 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography-Based Metabolic Habitats: A Multicenter Radiomic and Biological Study

Ann Surg Oncol, 2025

Open Access
Cited by 6
Prediction of lung cancer immunotherapy response via machine learning analysis of immune cell lineage and surface markers

Cancer Biomark, 2022

Open Access
Cited by 6
Prevalent findings on low-dose CT scan lung cancer screening: a French prospective pilot study

Eur J Public Health, 2025

Open Access
Cited by 6
Tertiary lymphoid structures gene signature predicts response to immunotherapy plus chemotherapy in advanced non-small cell lung cancer

Cancer Immunol Immunother, 2025

Open Access
Cited by 5
A radiomics-based machine learning model and SHAP for predicting spread through air spaces and its prognostic implications in stage I lung adenocarcinoma: a multicenter cohort study

Cancer Imaging, 2025

Open Access
Cited by 5
AI driven hybrid convolutional and transformer based deep learning architecture for precise lung nodule classification

Sci Rep, 2026

Open Access
Cited by 5
Artificial intelligence for lung cancer: a systematic review of head-to-head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis

BMC Med Imaging, 2026

Open Access
Cited by 5
Artificial intelligence-powered spatial analysis of tumor microenvironment in patients with non-small cell lung cancer with acquired resistance to EGFR tyrosine kinase inhibitor

J Immunother Cancer, 2025

Open Access
Cited by 5
Clinical validation of lightweight CNN architectures for reliable multi-class classification of lung cancer using histopathological imaging techniques

Sci Rep, 2026

Open Access
Cited by 5
Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model

Cancer Imaging, 2025

Open Access
Cited by 5
Computational analysis of whole slide images predicts PD-L1 expression and progression-free survival in immunotherapy-treated non-small cell lung cancer patients

J Transl Med, 2025

Open Access
Cited by 5
Concordance-based Predictive Uncertainty (CPU)-Index: proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT

Artif Intell Med, 2025

Open Access
Cited by 5
Construction of an automated machine learning-based predictive model for postoperative pulmonary complications risk in non-small cell lung cancer patients undergoing thoracoscopic surgery

PLoS One, 2025

Open Access
Cited by 5
Deep learning and inflammatory markers predict early response to immunotherapy in unresectable NSCLC: A multicenter study

Biomol Biomed, 2025

Open Access
Cited by 5
Deep Learning Approaches for Automated Prediction of Treatment Response in Non-Small-Cell Lung Cancer Patients Based on CT and PET Imaging

Tomography, 2025

Open Access
Cited by 5
Deep learning radiomics fusion model to predict visceral pleural invasion of clinical stage IA lung adenocarcinoma: a multicenter study

J Cardiothorac Surg, 2025

Open Access
Cited by 5
Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma

J Transl Med, 2025

Open Access
Cited by 5
Federated lung nodule segmentation using a hybrid transformer-U-Net architecture

Sci Rep, 2026

Open Access
Cited by 5
Full dimensional dynamic 3D convolution and point cloud in pulmonary nodule detection

J Adv Res, 2025

Open Access
Cited by 5
Harnessing local and system immune profiling delineating differential responders to first-line sintilimab (anti-PD-1 antibody) combined with chemotherapy in extensive-stage small cell lung cancer: an exploratory biomarker analysis of a phase II study

Signal Transduct Target Ther, 2025

Open Access
Cited by 5
Host and bacterial urine proteomics might predict treatment outcomes for immunotherapy in advanced non-small cell lung cancer patients

Front Immunol, 2025

Open Access
Cited by 5
Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images

J Imaging Inform Med, 2025

Open Access
Cited by 5
Leveraging multi-scale feature integration in UNet and FPN for semantic segmentation of lung nodules

Front Artif Intell, 2025

Open Access
Cited by 5
Lightweight Lung-nodule Detection Model Combined with Multidimensional Attention Convolution

Curr Med Imaging, 2025

Open Access
Cited by 5
Machine learning constructs a ferroptosis related signature for predicting prognosis and drug sensitivity in lung cancer

Cell Oncol (Dordr), 2025

Open Access
Cited by 5
Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis

BMC Cancer, 2025

Open Access
Cited by 5
Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach

PLoS One, 2025

Open Access
Cited by 5
RAU-Net for precise lung cancer GTV segmentation in radiation therapy planning

Sci Rep, 2025

Open Access
Cited by 5
Real-World Adherence Patterns of Comprehensive Genomic Profiling to Biomarker Recommended Therapies in Patients With Advanced Non-Small Cell Lung Cancer

JCO Oncol Pract, 2026

Open Access
Cited by 5
The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma

Front Immunol, 2025

Open Access
Cited by 5
Unraveling the molecular-pathological characteristics and cellular complexity of the tumor immune microenvironment in metastatic non-small cell lung cancer

Cell Commun Signal, 2025

Open Access
Cited by 5
Why Women Appear to Have Better Outcomes When Undergoing Screening for Lung Cancer

Ann Am Thorac Soc, 2025

Open Access
Cited by 4
A novel cancer-associated membrane signature predicts prognosis and therapeutic response for lung adenocarcinoma

Sci Rep, 2025

Open Access
Cited by 4
A novel deep learning framework for automatic scoring of PD-L1 expression in non-small cell lung cancer

Biomol Biomed, 2025

Open Access
Cited by 4
Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery

Zhongguo Fei Ai Za Zhi, 2025

Open Access
Cited by 4
Artificial intelligence-based deep learning algorithms for ground-glass opacity nodule detection: A review

Narra J, 2025

Open Access
Cited by 4
Cost-Efficient Early Diagnostic Tool for Lung Cancer: Explainable AI in Clinical Systems

Technol Cancer Res Treat, 2025

Open Access
Cited by 4
CT radiomics from intratumor and peritumor regions for predicting poorly differentiated invasive nonmucinous pulmonary adenocarcinoma

Sci Rep, 2025

Open Access
Cited by 4
DCAI: a dual cross-attention integration framework for benign-malignant classification of pulmonary nodules

Front Med (Lausanne), 2025

Open Access
Cited by 4
Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non-Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

JCO Precis Oncol, 2025

Open Access
Cited by 4
Development and validation of an interpretable machine learning model for predicting progression-free survival after immunotherapy in patients with non-small cell lung cancer: a multicenter study

Front Immunol, 2025

Open Access
Cited by 4
Development of a lung immune prognostic index-based nomogram model for predicting overall survival and immune-related adverse events in non-small cell lung cancer patients treated with sintilimab

Front Immunol, 2025

Open Access
Cited by 4
Digital Biomarkers for Precision Early Detection of Lung Cancer: Integrating AI-Driven Multi-Omics Into Clinical Pathways

Cancer Med, 2026

Open Access
Cited by 4
Evaluation of deep learning-based automated radiotherapy planning for early-stage lung cancer using SBRT-VMAT: A comparison with manual planning

J Appl Clin Med Phys, 2025

Open Access
Cited by 4
Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning

Cell Oncol (Dordr), 2024

Open Access
Cited by 4
Foundational Segmentation Models and Clinical Data Mining Enable Accurate Computer Vision for Lung Cancer

J Imaging Inform Med, 2025

Open Access
Cited by 4
Graph neural network model using radiomics for lung CT image segmentation

Sci Rep, 2025

Open Access
Cited by 4
Identification of STAT3 phosphorylation inhibitors using generative deep learning, virtual screening, molecular dynamics simulations, and biological evaluation for non-small cell lung cancer therapy

Mol Divers, 2025

Open Access
Cited by 4
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