ArticleNature communications2023
Deep learning to estimate lung disease mortality from chest radiographs.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Transparent chest radiograph foundation model enables explainable human disease profiling.NPJ digital medicine · 2026Article
- Can Artificial Intelligence Interpret Pulmonary Function Tests and Predict Prolonged Air Leaks After Lung Resection.Cancers · 2026Article
- Artificial Intelligence Tools in Precision Lung Cancer Care: From Early Detection to Clinical Decision Support.Cancers · 2026Review
- Artificial Intelligence in Lung Cancer: From Early Detection to Personalized Therapy.Current oncology reports · 2026Review
- Article
- A computationally frugal, open-source chest CT foundation model for thoracic disease detection in lung cancer screening programmes.Communications medicine · 2026Article
- Semi-supervised deep learning for uterus and bladder segmentation on female pelvic floor magnetic resonance imaging with limited labeled data.American journal of obstetrics and gynecology · 2026Article
- LDSC: enhancing lung disease diagnosis using a simple 1D-CNN.Scientific reports · 2026Article
- Mortality Prediction from Patient's First Day PAAC Radiograph in Internal Medicine Intensive Care Unit Using Artificial Intelligence Methods.Diagnostics (Basel, Switzerland) · 2025Article
- Chest X-Ray Foundation Model With Global and Local Representations Integration.IEEE transactions on medical imaging · 2025Article
- An intelligent diagnostic model for pulmonary nodules utilizing chest radiographic imagery and its application in community-based lung cancer screening.British journal of cancer · 2025Article
- LMeRAN: Label Masking-Enhanced Residual Attention Network for Multi-Label Chest X-Ray Disease Aided Diagnosis.Sensors (Basel, Switzerland) · 2025Article
- Oxidative Stress and Inflammation in Hypoxemic Respiratory Diseases and Their Comorbidities: Molecular Insights and Diagnostic Advances in Chronic Obstructive Pulmonary Disease and Sleep Apnea.Antioxidants (Basel, Switzerland) · 2025Review
- Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.European journal of medical research · 2025Review
- Deep learning to predict cardiovascular mortality from aortic disease in heavy smokers.NPJ cardiovascular health · 2024Article
- A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset.Scientific data · 2024Article
- Chest Radiographs as Biological Clocks: Implications for Risk Stratification and Personalized Care.Radiology. Artificial intelligence · 2024Article
- External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs.Radiology. Artificial intelligence · 2024Article
- Deep learning to predict long-term mortality from plain chest X-ray in patients referred for suspected coronary artery disease.Journal of thoracic disease · 2024Article
- Performing a Research Study Using Open-Source Deep Learning Models.Korean journal of radiology · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importance. While tests are available for reliable diagnosis, accurate identification of those who will develop severe morbidity/mortality is currently limited. Here, we developed a deep learning model, CXR Lung-Risk, to predict the risk of lung disease mortality from a chest x-ray. The model was trained using 147,497 x-ray images of 40,643 individuals and tested in three independent cohorts comprising 15,976 individuals. We found that CXR Lung-Risk showed a graded association with lung disease mortality after adjustment for risk factors, including age, smoking, and radiologic findings (Hazard ratios up to 11.86 [8.64-16.27]; p < 0.001). Adding CXR Lung-Risk to a multivariable model improved estimates of lung disease mortality in all cohorts. Our results demonstrate that deep learning can identify individuals at risk of lung disease mortality on easily obtainable x-rays, which may improve personalized prevention and treatment strategies.
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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.