ArticleScientific reports2020
Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 65 citations in OpenAlex.
- Artificial intelligence in pulmonary hypertension: a systematic review.European journal of medical research · 2025Pooled it
- A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).Medicina (Kaunas, Lithuania) · 2025Pooled it
- Comparative accuracy of artificial intelligence versus manual interpretation in detecting pulmonary hypertension across chest imaging modalities: a diagnostic test accuracy meta-analysis.Frontiers in artificial intelligence · 2025Pooled it
- Radiological assessment of pulmonary vascularity in congenital heart disease: standardized clinician assessment versus deep learning-based prediction.Journal of cardiovascular imaging · 2026Article
- Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network.Journal of imaging informatics in medicine · 2026Article
- Artificial Intelligence in Pulmonary Hypertension: Current State and Future Prospects.Reviews in cardiovascular medicine · 2026Review
- Observational
- Integrating multimodal intelligence in heart failure: AI-driven risk prediction, precision diagnosis, phenotyping, personalized treatment, and prognosis.Chinese medical journal · 2026Review
- Performance of Guideline-Recommended Approaches to Echocardiographic Investigation for Pulmonary Hypertension: Analysis of the CIPHER Study.Pulmonary circulation · 2026Article
- Chest Computed Tomography-Based Radiomics for the Diagnosis and Prognosis of Pulmonary Hypertension.Journal of the American Heart Association · 2025Article
- The role of artificial intelligence and mobile health in diagnosis and management of pulmonary arterial hypertension.International journal of cardiology. Congenital heart disease · 2025Review
- Therapeutic targets for pulmonary arterial hypertension: insights into the emerging landscape.Expert opinion on therapeutic targets · 2025Review
- Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension.NPJ digital medicine · 2025Article
- A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension.Journal of imaging informatics in medicine · 2025Article
- An ensemble learning model for detection of pulmonary hypertension using electrocardiogram, chest X-ray, and brain natriuretic peptide.European heart journal. Digital health · 2025Article
- Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.Journal of the American Heart Association · 2025Article
- A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach.Computational and structural biotechnology journal · 2024Article
- Deep learning prediction of survival in patients with heart failure using chest radiographs.The international journal of cardiovascular imaging · 2024Article
- An electrocardiogram-based AI algorithm for early detection of pulmonary hypertension.The European respiratory journal · 2024Article
- Revolutionizing Cardiology through Artificial Intelligence-Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment-A Comprehensive Review of the Past 5 Years.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify elevated pulmonary artery pressure (PAP) and stratify the risk of heart failure hospitalization with PH. We retrospectively enrolled a total of 900 consecutive patients with suspected PH. We trained a convolutional neural network to identify patients with elevated PAP (> 20 mmHg) as the actual value of PAP. The endpoints in this study were admission or occurrence of heart failure with elevated PAP. In an independent evaluation set for detection of elevated PAP, the area under curve (AUC) by the AI algorithm was significantly higher than the AUC by measurements of CXR images and human observers (0.71 vs. 0.60 and vs. 0.63, all p < 0.05). In patients with AI predicted PH had 2-times the risk of heart failure with PH compared with those without AI predicted PH. This preliminary work suggests that applying AI to the CXR in high risk groups has limited performance when used alone in identifying elevated PAP. We believe that this report can serve as an impetus for a future large study.
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