ArticleFrontiers in oncology2020
Clinical, Conventional CT and Radiomic Feature-Based Machine Learning Models for Predicting ALK Rearrangement Status in Lung Adenocarcinoma Patients.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 77 citations in OpenAlex.
- 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.European radiology · 2026Pooled it
- AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Individualized nomogram for predicting ALK rearrangement status in lung adenocarcinoma patients.European radiology · 2021Trial
- Imaging the hallmarks of cancer.Nature reviews. Cancer · 2026Review
- Noninvasive prediction of ALK fusion status in non-small cell lung cancer by a machine learning model combining CT images and clinical information.Journal of thoracic disease · 2026Article
- Deep learning-based CT radiomics for ALK rearrangement status prediction in lung adenocarcinoma.BMC cancer · 2026Article
- Design and synthesis of novel Osimertinib analogs for dual EGFR and P-glycoprotein 1 inhibition targeting multidrug resistance in non-small cell lung cancer: In vitro and in vivo evaluation.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Radiology-based artificial intelligence for predicting targeted therapy response in pan-cancer: a comprehensive review.Journal of translational medicine · 2025Review
- Radiogenomics: transforming lung cancer care through non-invasive imaging and genomic integration.Medical oncology (Northwood, London, England) · 2025Review
- Radiomics and radiogenomics in ovarian cancer: a review with a focus on ultrasound applications.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Review
- Intratumoral and peritumoral CT radiomics in predicting anaplastic lymphoma kinase mutations and survival in patients with lung adenocarcinoma: a multicenter study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- An Enhanced CT-based Radiomics Model for Predicting the Anaplastic Lymphoma Kinase Mutation Status in Lung Adenocarcinoma.Current medical imaging · 2025Article
- Imaging patterns and recommendations for diagnosis, staging, and management of lung cancer.BJR open · 2025Review
- Predicting the severity of mycoplasma pneumoniae pneumonia in pediatric and adult patients: a multicenter study.Scientific reports · 2024Article
- Radiogenomics models for predicting prognosis in locally advanced non-small cell lung cancer patients undergoing definitive chemoradiotherapy.Translational lung cancer research · 2024Article
- Predictive value of delta-radiomic features for prognosis of advanced non-small cell lung cancer patients undergoing immune checkpoint inhibitor therapy.Translational lung cancer research · 2024Article
- PredictingTranslational lung cancer research · 2024Article
- Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry.Journal of personalized medicine · 2024Review
- CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.Military Medical Research · 2024Article
- 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
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.