ReviewRespiration; international review of thoracic diseases
The Emerging Role of Radiomics in COPD and Lung Cancer.
Review in Respiration; international review of thoracic diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
30 citing papers in PubMed, 50 citations in OpenAlex.
- Radiomic analysis of computed tomography scans in COPD patients relates to different clinical and biological features, and identifies different lung function trajectories during follow-up.ERJ open research · 2026Article
- Cancer classification with radiomics in controlled preclinical models.Scientific reports · 2026Article
- Predictive value of CT target scan-based radiomics and clinical features for patients with chronic obstructive pulmonary disease combined with malignant pulmonary nodules.Biomedical engineering online · 2026Article
- Evaluation of unified harmonization of CT images across multiple tasks: A step towards AI generalizability.Medical physics · 2025Article
- Automatic recognition and differentiation of pulmonary contusion and bacterial pneumonia based on deep learning and radiomics.BMC medical imaging · 2025Article
- Prediction of Radiation Therapy Induced Cardiovascular Toxicity from Pretreatment CT Images in Patients with Thoracic Malignancy via an Optimal Biomarker Approach.Academic radiology · 2025Article
- Article
- Unveiling the Influence of AI on Advancements in Respiratory Care: Narrative Review.Interactive journal of medical research · 2024Review
- Radiomics in radiology: What the radiologist needs to know about technical aspects and clinical impact.La Radiologia medica · 2024Review
- Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.BMC pulmonary medicine · 2024Article
- Article
- Quantitative computed tomography and visual emphysema scores: association with lung function decline.ERJ open research · 2023Article
- Multi-Layer Perceptron Classifier with the Proposed Combined Feature Vector of 3D CNN Features and Lung Radiomics Features for COPD Stage Classification.Journal of healthcare engineering · 2023Article
- Lung Radiomics Features Selection for COPD Stage Classification Based on Auto-Metric Graph Neural Network.Diagnostics (Basel, Switzerland) · 2022Article
- A Handcrafted Radiomics-Based Model for the Diagnosis of Usual Interstitial Pneumonia in Patients with Idiopathic Pulmonary Fibrosis.Journal of personalized medicine · 2022Article
- Early COPD Risk Decision for Adults Aged From 40 to 79 Years Based on Lung Radiomics Features.Frontiers in medicine · 2022Article
- Development and Validation of a Radiomics Nomogram Using Computed Tomography for Differentiating Immune Checkpoint Inhibitor-Related Pneumonitis From Radiation Pneumonitis for Patients With Non-Small Cell Lung Cancer.Frontiers in immunology · 2022Article
- Multi-modal data combination strategy based on chest HRCT images and PFT parameters for intelligent dyspnea identification in COPD.Frontiers in medicine · 2022Article
- Artificial intelligence assists precision medicine in cancer treatment.Frontiers in oncology · 2022Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineable data, by extracting and correlating quantitative imaging features with patients' outcomes and tumor phenotype - a process termed radiomics. While this process has already been widely researched in lung oncology, the evaluation of COPD in this fashion remains in its infancy. Here we outline the main applications of radiomics in lung cancer and briefly review the workflow from image acquisition to the evaluation of model performance. Finally, we discuss the current assessments of COPD and the potential application of radiomics in COPD.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.