ArticleNature medicine2019
Author Correction: End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.
Article in Nature medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis 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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global research trends in the application of artificial intelligence in oncology care: a bibliometric study.Frontiers in oncology · 2024Pooled it
- Multi-task learning for predicting pulmonary nodule growth and follow-up volume.Frontiers in oncology · 2026Article
- Artificial intelligence-assisted ultrasound screening for breast cancer in China: a prospective, clustered, controlled, population-based study.Breast cancer research : BCR · 2025Article
- Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.Scientific reports · 2025Article
- Deep learning on T2WI to predict the muscle-invasive bladder cancer: a multi-center clinical study.Scientific reports · 2025Article
- Development of a nomogram-based model incorporating radiomic features from follow-up longitudinal lung CT images to distinguish invasive adenocarcinoma from benign lesions: a retrospective study.BMC pulmonary medicine · 2024Article
- Preliminary experiments on interpretable ChatGPT-assisted diagnosis for breast ultrasound radiologists.Quantitative imaging in medicine and surgery · 2024Article
- Value of radiomics and deep learning feature fusion models based on dce-mri in distinguishing sinonasal squamous cell carcinoma from lymphoma.Frontiers in oncology · 2024Article
- The deep learning radiomics nomogram helps to evaluate the lymph node status in cervical adenocarcinoma/adenosquamous carcinoma.Frontiers in oncology · 2024Article
- Multi-Modal Feature Fusion-Based Multi-Branch Classification Network for Pulmonary Nodule Malignancy Suspiciousness Diagnosis.Journal of digital imaging · 2023Article
- A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning.Sensors (Basel, Switzerland) · 2023Article
- Deep learning-based algorithm improves radiologists' performance in lung cancer bone metastases detection on computed tomography.Frontiers in oncology · 2023Article
- Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.Radiology · 2022Article
- Investigation of small lung lesion detection for lung cancer screening in low dose FDG PET imaging by deep neural networks.Frontiers in public health · 2022Article
- Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.Nature machine intelligence · 2021Article
- Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine.Cold Spring Harbor perspectives in medicine · 2021Review
- Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.JAMA network open · 2020Article
- Article
Corrections and comments
- Erratum for
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Identifiers
31253948What 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.