ReviewFrontiers in oncology2024
PET/CT radiomics and deep learning in the diagnosis of benign and malignant pulmonary nodules: progress and challenges.
Review in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Innovative technologies and their clinical prospects for early lung cancer screening.Clinical and experimental medicine · 2025Pooled it
- Stage-stratified benefits of AI-radiomics PET in early Alzheimer's disease: a systematic review and meta-analysis.Frontiers in neurologyPooled it
- Combined Model Integrating Clinical-Imaging and Deep Learning to Discriminate Between Persistent Inflammatory and Malignant Subsolid Pulmonary Nodules.Journal of imaging informatics in medicine · 2026Article
- Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.European radiology · 2026Article
- Comparison of clinical-radiological and radiomics features for predicting pulmonary nodule malignancy in a multicenter study of mixed clinical and surveillance populations.European radiology · 2026Article
- Improving risk stratification of pulmonary nodules: an integrated perinodular vascular and radiomic model for clinical decision support.BMC medical imaging · 2026Article
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Synchronous lung adenocarcinomaFrontiers in oncology · 2026Article
- Completion lobectomy following segmentectomy for malignant lung tumors: a multi-institutional study of surgical feasibility, oncologic outcomes, and diagnostic challenges (ESSG-02 study).Translational lung cancer research · 2025Article
- Fusion of 2.5D deep transfer learning and radiomics for predicting benign and malignant Lung Imaging Reporting and Data System (Lung-RADS) 3 and 4A nodules.Journal of thoracic disease · 2025Article
- Review
- The study of dual-phaseScientific reports · 2025Article
- Effect of reconstruction settings on radiomics feature robustness in positron emission tomography images: a clinical study.Quantitative imaging in medicine and surgery · 2025Article
- Flexible Bronchoscopy and Non-Small-Cell Lung Cancer Staging: A Narrative Review of Modern Techniques for Optimized Clinical Decision-Making.Journal of clinical medicine · 2025Review
- Development and validation of CT radiomics diagnostic models: differentiating benign from malignant pulmonary nodules and evaluating malignancy degree.Journal of thoracic disease · 2025Article
- Experiences of health information-seeking behaviour in preoperative patients with lung cancer: a qualitative study in China.BMJ open · 2025Article
- Machine learning assisted breathomic approach for early-stage thoracic cancer detection.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is currently the leading cause of cancer-related deaths, and early diagnosis and screening can significantly reduce its mortality rate. Since some early-stage lung cancers lack obvious clinical symptoms and only present as pulmonary nodules (PNs) in imaging examinations, accurately determining the benign or malignant nature of PNs is crucial for improving patient survival rates.
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Identifiers
What Socratic holds
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 Socratic graph.