ArticleScientific reports2022
Prediction of malignant lymph nodes in NSCLC by machine-learning classifiers using EBUS-TBNA and PET/CT.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.BMC pulmonary medicine · 2025Pooled it
- Recent Updates on Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration and Its Clinical Implications.Tuberculosis and respiratory diseases · 2026Review
- Applications of Artificial Intelligence in Endobronchial Ultrasound for Lung Cancer Diagnosis and Staging: A Scoping Review.Current oncology (Toronto, Ont.) · 2026Article
- [18F]FDG-PET/CT-based evaluation of tumor response kinetics during induction chemotherapy and concurrent radiochemotherapy in stage II - III small-cell lung cancer.European journal of nuclear medicine and molecular imaging · 2026Article
- Case Report: How to tailor adjuvant radiotherapy after open partial laryngeal surgery in the setting of a secure R0-resection?Frontiers in oncology · 2026Article
- Pathologic Complete Response Predicts Long-Term Survival Following Neoadjuvant Induction Chemotherapy and Chemo-Radiotherapy in Stage-III Non-Small Cell Lung Cancer.Thoracic cancer · 2025Article
- Review
- Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.PloS one · 2025Article
- C-reactive protein as robust laboratory value associated with prognosis in patients with stage III non-small cell lung cancer (NSCLC) treated with definitive radiochemotherapy.Scientific reports · 2024Article
- Advances in lymphatic metastasis of non-small cell lung cancer.Cell communication and signaling : CCS · 2024Review
- Machine Learning and Texture Analysis of [Biomedicines · 2024Article
- Understand how machine learning impact lung cancer research from 2010 to 2021: A bibliometric analysis.Open medicine (Warsaw, Poland) · 2024Article
- Machine learning approaches in the interpretation of endobronchial ultrasound images: a comparative analysis.Surgical endoscopy · 2023Article
- Lung Cancer Staging: Imaging and Potential Pitfalls.Diagnostics (Basel, Switzerland) · 2023Review
- Distinguishing bronchoscopically observed anatomical positions of airway under by convolutional neural network.Therapeutic advances in chronic disease · 2023Article
- The different manifestations ofFrontiers in nuclear medicine · 2022Article
- Science progress distinguishing different types of airway stents under bronchoscopy by artificial intelligence.Science progressArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate determination of lymph-node (LN) metastases is a prerequisite for high precision radiotherapy. The primary aim is to characterise the performance of PET/CT-based machine-learning classifiers to predict LN-involvement by endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) in stage-III NSCLC. Prediction models for LN-positivity based on [
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.