ArticleAnnals of translational medicine2017
Lung cancer screening with low dose CT and radiation harm-from prediction models to cancer incidence data.
Article in Annals of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Peutz-Jeghers Syndrome and lung cancer: does the risk meet the threshold for lung cancer screening?Familial cancer · 2026Review
- From Lung Cancer Predictive Models toJournal of clinical medicine · 2026Review
- Cancer risk associated with CT imaging: quantifying the evidence, addressing misconceptions, and optimizing risk communication.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2026Review
- Photon-Counting Computed Tomography in Thoracic Surgery: A Narrative Review of Current and Future Applications.Cancers · 2025Review
- Model-Based Cost-Utility Analysis of Combined Low-Dose Computed Tomography Screening for Lung Cancer, Chronic Obstructive Pulmonary Disease, and Cardiovascular Disease.JTO clinical and research reports · 2025Article
- Lung Cancer Screening with Low-Dose CT: What We Have Learned in Two Decades of ITALUNG and What Is Yet to Be Addressed.Diagnostics (Basel, Switzerland) · 2023Review
- Radiation dose reduction using deep learning-based image reconstruction for a low-dose chest computed tomography protocol: a phantom study.Quantitative imaging in medicine and surgery · 2023Article
- Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions.Life (Basel, Switzerland) · 2022Review
- Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome.International journal of molecular sciences · 2022Review
- Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancerFrontiers in medicine · 2022Review
- Article
- LDCT Screening in Smokers in India-A Pilot, Proof-of-Concept Study.The Indian journal of radiology & imaging · 2021Article
- Dosimetry and Comparison between Different CT Protocols (Low Dose, Ultralow Dose, and Conventional CT) for Lung Nodules' Detection in a Phantom.Radiology research and practice · 2021Article
- Article
- Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data.European journal of epidemiology · 2020Article
- DeepLN: an artificial intelligence-based automated system for lung cancer screening.Annals of translational medicine · 2020Article
- Retrospective analysis of 1118 outpatient chest CT scans to determine factors associated with excess scan length.Clinical imaging · 2020Article
- Improved discrimination between benign and malignant LDCT screening-detected lung nodules with dynamic over staticPhysics in medicine and biology · 2018Article
- Cost-Efficient Early Diagnostic Tool for Lung Cancer: Explainable AI in Clinical Systems.Technology in cancer research & treatmentArticle
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2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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.