ArticleScientific reports2022
Detection of acute thoracic aortic dissection based on plain chest radiography and a residual neural network (Resnet).
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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14 citing papers in PubMed, 19 citations in OpenAlex.
- AI-driven diagnosis of acute aortic syndrome based on multi-modal information fusion.Scientific reports · 2026Article
- Deep learning in the early diagnosis of acute aortic dissection.Frontiers in cardiovascular medicine · 2026Review
- Performance of image-based deep learning models for aortic dissection segmentation and diagnosis: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2026Review
- Chest X-Ray as a Screening Tool for Aortic Arch Dilation: CT-Based Evaluation of Reliability.Diagnostics (Basel, Switzerland) · 2025Article
- Artificial intelligence-driven diagnosis of acute thoracic aortic dissection: integrating imaging, biomarkers, and clinical workflows-a narrative review.Annals of translational medicine · 2025Review
- Deep learning-aided diagnosis of acute abdominal aortic dissection by ultrasound images.Emergency radiology · 2025Article
- Non-Inferiority Analysis of Electrocardiography Analysis Application vs. Point-of-Care Ultrasound for Screening Left Ventricular Dysfunction.Yonsei medical journal · 2025Article
- Streamlining Acute Abdominal Aortic Dissection Management-An AI-based CT Imaging Workflow.Journal of imaging informatics in medicine · 2024Article
- Explainable artificial intelligence in deep learning-based detection of aortic elongation on chest X-ray images.European heart journal. Digital health · 2024Article
- Article
- Identifying patients with acute aortic dissection using an electrocardiogram with convolutional neural network.International journal of cardiology. Heart & vasculature · 2024Article
- Residual networks models detection of atrial septal defect from chest radiographs.La Radiologia medica · 2024Article
- Artificial Intelligence-Based Prediction of Cardiovascular Diseases from Chest Radiography.Journal of imaging · 2023Review
- Dual spin max pooling convolutional neural network for solar cell crack detection.Scientific reports · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute thoracic aortic dissection is a life-threatening disease, in which blood leaking from the damaged inner layer of the aorta causes dissection between the intimal and adventitial layers. The diagnosis of this disease is challenging. Chest x-rays are usually performed for initial screening or diagnosis, but the diagnostic accuracy of this method is not high. Recently, deep learning has been successfully applied in multiple medical image analysis tasks. In this paper, we attempt to increase the accuracy of diagnosis of acute thoracic aortic dissection based on chest x-rays by applying deep learning techniques. In aggregate, 3,331 images, comprising 716 positive images and 2615 negative images, were collected from 3,331 patients. Residual neural network 18 was used to detect acute thoracic aortic dissection. The diagnostic accuracy of the ResNet18 was observed to be 90.20% with a precision of 75.00%, recall of 94.44%, and F1-score of 83.61%. Further research is required to improve diagnostic accuracy based on aorta segmentation.
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