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References from Multimodal AI for early lung cancer detection: from LDCT to clinical and molecular integration. Local targets link to admitted publications; unresolved targets remain external evidence.
Cancer statistics, 2026
2026 · External reference
Identifying optimal first-line treatment for advanced non-small cell lung carcinoma with high PD-L1 expression: a matter of debate
10.1038/s41416-022-01929-w · 2022 · External reference
Role of PD-L1 assessment in advanced NSCLC: does it still matter?
10.1097/cad.0000000000001118 · 2021 · External reference
Sex differences in adverse events among cancer patients receiving immune checkpoint inhibitors: the MOUSEION-07 systematic review and meta-analysis
2024 · External reference
Reduced lung-cancer mortality with low-dose computed tomographic screening
2026 · External reference
Reduced lung-cancer mortality with volume CT screening in a randomized trial
10.1056/nejmoa1911793 · 2020 · External reference
Limitations of screening for lung cancer with low-dose spiral computed tomography
10.1158/1078-0432.ccr-05-9000 · 2005 · External reference
Barriers to completing low dose computed tomography scan for lung cancer screening
10.1016/j.cllc.2024.04.014 · 2024 · External reference
Contemporary issues in the implementation of lung cancer screening
2021 · External reference
The regimen of computed tomography screening for lung Cancer: lessons learned over 25 years from the international early lung cancer action program
10.1097/rti.0000000000000538 · 2021 · External reference
Assessing lung cancer absolute risk trajectory based on a polygenic risk model
10.1158/0008-5472.can-20-1237 · 2021 · External reference
Integrating deep learning of low-dose CT imaging with clinical data for lung cancer risk prediction
10.1016/j.chest.2026.02.022 · 2026 · External reference
Radiomics for dynamic lung cancer risk prediction in uspstf-ineligible patients
2025 · External reference
An early lung cancer diagnosis model for non-smokers incorporating ct imaging analysis and circulating genetically abnormal cells (CACs)
10.1186/s12885-024-13268-5 · 2025 · External reference
Transient asymptomatic pulmonary opacities and interstitial lung disease in EGFR-mutated non-small cell lung cancer treated with osimertinib
10.1177/03008916211047888 · 2022 · External reference
Biomarkers in lung cancer screening: achievements, promises, and challenges
10.1016/j.jtho.2018.11.023 · 2019 · External reference
Molecular biomarkers in early stage lung cancer
10.21037/tlcr-20-750 · 2021 · External reference
Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis
2026 · External reference
Innovative technologies and their clinical prospects for early lung cancer screening
10.1007/s10238-025-01752-6 · 2025 · External reference
A 20-year Follow-up of the international early lung cancer action program (I-ELCAP)
2023 · External reference
Survival of patients with stage i lung cancer detected on CT screening
10.1056/nejmoa060476 · 2006 · External reference
Hyponatremia in cancer patients receiving immune checkpoint inhibitors: the ARON-MOUSEION-014 meta-analysis
2026 · External reference
Infusion-Related reactions among cancer patients receiving immune checkpoint Inhibitors: the ARON-MOUSEION-013 systematic review and meta-analysis
10.2147/dddt.s560518 · 2025 · External reference
Massion P. risk stratification of indeterminate pulmonary nodules
10.1097/mcp.0000000000000780 · 2021 · External reference
ACR Lung-RADS v2022: assessment categories and management recommendations
10.1016/j.jacr.2023.09.009 · 2024 · External reference
British thoracic society guidelines for the investigation and management of pulmonary nodules
10.1136/thoraxjnl-2015-207168 · 2015 · External reference
Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd Ed: american college of chest physicians evidence-based clinical practice guidelines
10.1378/chest.12-2351 · 2013 · External reference
Improving lung cancer diagnosis with cancer, fungal, and imaging biomarkers
10.1016/j.jtcvs.2022.12.014 · 2023 · External reference
Improving malignancy risk prediction of indeterminate pulmonary nodules with imaging features and biomarkers
10.1016/j.cca.2022.07.010 · 2022 · External reference
Tutorial: a guide to performing polygenic risk score analyses
10.1038/s41596-020-0353-1 · 2020 · External reference
Sybil: a validated deep learning model to predict future lung cancer risk from a single low-dose chest computed tomography
10.1200/jco.22.01345 · 2023 · External reference
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
10.1038/s41591-019-0447-x · 2019 · External reference
Diagnostic test accuracy of artificial intelligence-based imaging for lung cancer screening: a systematic review and meta-analysis
10.1016/j.lungcan.2022.12.002 · 2023 · External reference
The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence
10.1038/s41591-025-03953-8 · 2025 · External reference
The image biomarker standardization Initiative: standardized quantitative radiomics for high-throughput Image-based phenotyping
10.1148/radiol.2020191145 · 2020 · External reference
Challenges and best practices when using ComBAT to harmonize diffusion MRI data
2025 · External reference
A guide to combat harmonization of imaging biomarkers in multicenter studies
10.2967/jnumed.121.262464 · 2022 · External reference
Performance comparison of modified combat for harmonization of radiomic features for multicenter studies
2020 · External reference
Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study
10.1007/s00330-019-06597-8 · 2020 · External reference
Radiomic “Stress Test”: exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort
2025 · External reference
Reducing uncertainty in cancer risk estimation for patients with indeterminate pulmonary nodules using an integrated deep learning model
2022 · External reference
Development and validation of a CT-based comprehensive nomogram for differentiating benign from malignant subcentimeter solid nodules
10.21037/jtd-2025-618 · 2025 · External reference
Development and validation of a multimodal radiomics-serum biomarker model for diagnosing solid pulmonary nodules via machine learning
10.21037/jtd-2025-1214 · 2025 · External reference
Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning
2024 · External reference
Prediction of single pulmonary nodule growth by CT radiomics and clinical features - a one-year follow-up study
2022 · External reference
Clinical value of combining molecular and immune blood tests to safely reduce false positives in low-dose computed tomography lung cancer screening
2026 · External reference
Detection and characterization of lung cancer using cell-free DNA fragmentomes
10.1038/s41467-021-24994-w · 2021 · External reference
Cell-Free DNA fragmentomes in the diagnostic evaluation of patients with symptoms suggestive of lung cancer
10.1016/j.chest.2023.04.033 · 2023 · External reference
Clinical validation of a cell-free DNA fragmentome assay for augmentation of lung cancer early detection
10.1158/2159-8290.cd-24-0519 · 2024 · External reference
Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study (DECIPHER-NODL)
2025 · External reference
Cost-effective shallow genome-wide sequencing for profiling plasma cfdna signatures to enhance lung cancer detection
10.1080/14796694.2025.2483154 · 2025 · External reference
Cell-free epigenomes enhanced fragmentomics-based model for early detection of lung cancer
2025 · External reference
Fragments of a story: could mitochondrial DNA fragmentomics upend lung cancer early diagnosis?
10.1164/rccm.202508-1874ed · 2026 · External reference
Validation of lung EpiCheck, a novel methylation-based blood assay, for the detection of lung cancer in european and chinese high-risk individuals
2021 · External reference
Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study
10.1016/s2589-7500(23)00125-5 · 2023 · External reference
A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules
2024 · External reference
Development and validation of an integrated system for lung cancer screening and post-screening pulmonary nodules management: a proof-of-concept study (ASCEND-LUNG)
2024 · External reference
A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer
10.21147/j.issn.1000-9604.2023.05.08 · 2023 · External reference
A prediction model based on DNA methylation biomarkers and radiological characteristics for identifying malignant from benign pulmonary nodules
10.1186/s12885-021-08002-4 · 2021 · External reference
Multimodal modeling based on DNA methylation analysis in bronchoalveolar lavage fluid for early lung cancer detection
2026 · External reference
A classifier for improving early lung cancer diagnosis incorporating artificial intelligence and liquid biopsy
2022 · External reference
Diagnostic value of circulating genetically abnormal cells to support computed tomography for benign and malignant pulmonary nodules
10.1186/s12885-022-09472-w · 2022 · External reference
Fusion of CT radiomics and autoantibody biomarkers for enhanced prediction of lung cancer diagnosis: a comprehensive study
2025 · External reference
Multiple Tumor-related autoantibodies test enhances CT-based deep learning performance in diagnosing lung cancer with diameters < 70 mm: a prospective study in china
10.1186/s12890-025-03807-6 · 2025 · External reference
Exploratory algorithms to aid in risk of malignancy prediction for indeterminate pulmonary nodules
2025 · External reference
Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data
2023 · External reference
A predictive model integrating AI recognition technology and biomarkers for lung nodule assessment
10.1055/a-2446-9832 · 2025 · External reference
Enhancing diagnosis of benign lesions and lung cancer through ensemble text and breath analysis: a retrospective cohort study
10.1038/s41598-024-59474-w · 2024 · External reference
Differentiating pulmonary nodule malignancy using exhaled volatile organic Compounds: a prospective observational study
2025 · External reference
Real-time breath metabolomics as catalyst for personalized lung cancer diagnostics: prospective matched case-control trial (LUCAbreath)
2026 · External reference
Combining low-dose computer-tomography-based radiomics and serum metabolomics for diagnosis of malignant nodules in participants of lung cancer screening studies
2023 · External reference
Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging features
10.1186/s12967-024-05723-5 · 2024 · External reference
Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls
10.1002/cncr.35130 · 2024 · External reference
A multivariate cell-based liquid biopsy for lung nodule risk stratification: analytical validation and early clinical evaluation
2025 · External reference
Auxiliary diagnosis of pulmonary Nodules’ benignancy and malignancy based on machine Learning: a retrospective study
10.2147/jmdh.s518166 · 2025 · External reference
A multiomics dataset of paired CT image and plasma cell-free DNA end motif for patients with pulmonary nodules
10.1038/s41597-025-04912-1 · 2025 · External reference
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
2024 · External reference
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
2022 · External reference
Adherence to TRIPOD+AI guideline: an updated reporting assessment tool
2026 · External reference
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
10.1080/13696998.2024.2444781 · 2025 · External reference
