ArticleNature communications2023
Interstitial lung disease diagnosis and prognosis using an AI system integrating longitudinal data.
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 45 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.
- A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Diagnosing Solid Lesions in the Pancreas With Multimodal Artificial Intelligence: A Randomized Crossover Trial.JAMA network open · 2024Trial
- Prognostic impact of autoimmune features in interstitial lung disease: a single-center retrospective real-world cohort study.Clinical rheumatology · 2026Article
- Nomogram models integrating multiregion radiomics, quantitative computed tomography, and clinical indicators for distinguishing connective tissue disease-associated interstitial lung disease from idiopathic pulmonary fibrosis and improving the prediction of gender-age-physiology stage.Quantitative imaging in medicine and surgery · 2026Article
- A Systematic Review of Deep Learning and Machine Learning Applications in Longitudinal Multimodal Clinical Data.Journal of healthcare informatics research · 2026Review
- Admission-Based Machine-Learning Models for Predicting Mechanical Ventilation and Mortality in Fibrotic Interstitial Lung Disease: A Multicenter Cohort Study with External Validation.Balkan medical journal · 2026Article
- Letter to the Editor: CT-guided lung biopsy in patients with interstitial lung abnormalities.European radiology · 2026Article
- Retinal imaging and supervised learning predict hospitalizations and kidney and heart-lung damage in sickle cell disease.Blood advances · 2026Observational
- Development of a multimodal large language model for early warning and diagnosis of chronic ocular GVHD.NPJ digital medicine · 2026Article
- An analysis of clinical manifestations and therapeutic outcomes in pediatric connective tissue disease-associated interstitial lung disease.Pediatric rheumatology online journal · 2026Article
- LDSC: enhancing lung disease diagnosis using a simple 1D-CNN.Scientific reports · 2026Article
- Non-contact lung disease classification via orthogonal frequency division multiplexing-based passive 6G integrated sensing and communication.Communications medicine · 2026Article
- Artificial intelligence in idiopathic pulmonary fibrosis: advances, challenges and future directions.The European respiratory journal · 2026Review
- A transfer learning-based multimodal model for early prediction of 90-day respiratory failure in dermatomyositis-associated interstitial lung disease.Frontiers in immunology · 2026Article
- Contemporary management of sarcoidosis.Frontiers in medicine · 2026Review
- Targeted Therapy-Induced Interstitial Lung Disease in NSCLC: Mechanisms, Clinical Signatures, and a Precision Medicine Roadmap.Drug design, development and therapy · 2026Review
- AI in radiology and interventions: a structured narrative review of workflow automation, accuracy, and efficiency gains of today and what's coming.International journal of computer assisted radiology and surgery · 2026Review
- The role of multidisciplinary discussion in diagnosis and management of interstitial lung diseases: a retrospective evaluation of a single-center 10 years' of experience.La Radiologia medica · 2026Observational
- Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data.IEEE reviews in biomedical engineering · 2026Review
- A lung CT vision foundation model facilitating disease diagnosis and medical imaging.Nature communications · 2025Article
Corrections and comments
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Authors and funding
22 authors at 3 institutions in 1 country.
Funding
Abstract
For accurate diagnosis of interstitial lung disease (ILD), a consensus of radiologic, pathological, and clinical findings is vital. Management of ILD also requires thorough follow-up with computed tomography (CT) studies and lung function tests to assess disease progression, severity, and response to treatment. However, accurate classification of ILD subtypes can be challenging, especially for those not accustomed to reading chest CTs regularly. Dynamic models to predict patient survival rates based on longitudinal data are challenging to create due to disease complexity, variation, and irregular visit intervals. Here, we utilize RadImageNet pretrained models to diagnose five types of ILD with multimodal data and a transformer model to determine a patient's 3-year survival rate. When clinical history and associated CT scans are available, the proposed deep learning system can help clinicians diagnose and classify ILD patients and, importantly, dynamically predict disease progression and prognosis.
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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.