Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
- Emergency department visits for chest pain and abdominal pain: United States, 1999-2008.NCHS Data Brief. 2010; : 1-8
- Testing of low-risk patients presenting to the emergency department with chest pain: a scientific statement from the American Heart Association.Circulation. 2010; 122: 1756-1776
- Insights from the International Registry of Acute Aortic Dissection: a 20-year experience of collaborative clinical research.Circulation. 2018; 137: 1846-1860
- The risk of misdiagnosis in acute thoracic aortic dissection: a review of current guidelines.Heart. 2020; 106: 885-891
- Correlates of delayed recognition and treatment of acute type A aortic dissection: the International Registry of Acute Aortic Dissection (IRAD).Circulation. 2011; 124: 1911-1918
- Misdiagnosis of aortic dissection: experience of 361 patients.J Clin Hypertens (Greenwich). 2012; 14: 256-260
- Frequency of and inappropriate treatment of misdiagnosis of acute aortic dissection.Am J Cardiol. 2007; 99: 852-856
- 2014 ESC Guidelines on the diagnosis and treatment of aortic diseases: document covering acute and chronic aortic diseases of the thoracic and abdominal aorta of the adult. The Task Force for the Diagnosis and Treatment of Aortic Diseases of the European Society of Cardiology (ESC).Eur Heart J. 2014; 35: 2873-2926
- Patients with type a acute aortic dissection presenting with an abnormal electrocardiogram.Ann Thorac Surg. 2018; 105: 92-99
- Chest radiography for the diagnosis of acute aortic syndrome.Am J Med. 2004; 116: 73-77
- The diagnostic accuracy of the mediastinal width on supine anteroposterior chest radiographs with nontraumatic Stanford type A acute aortic dissection.J Gen Fam Med. 2018; 19: 45-49
- A guide to deep learning in healthcare.Nat Med. 2019; 25: 24-29
- Deep learning.Nature. 2015; 521: 436-444
- Age and sex estimation using artificial intelligence from standard 12-lead ECGs.Circ Arrhythm Electrophysiol. 2019; 12e007284
- An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.Lancet. 2019; 394: 861-867
- Artificial intelligence in radiology.Nat Rev Cancer. 2018; 18: 500-510
- A deep-learning algorithm (ECG12Net) for detecting hypokalemia and hyperkalemia by electrocardiography: algorithm development.JMIR Med Inform. 2020; 8e15931
- Deep learning for chest radiograph diagnosis: a retrospective comparison of the CheXNeXt algorithm to practicing radiologists.PLoS Med. 2018; 15e1002686
Huang G, Liu Z, Van Der Maaten L, Weinberger KQ. Densely connected convolutional networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2017;2261-2269.
- ImageNet classification with deep convolutional neural networks. Proceedings of the 25th International Conference on Neural Information Processing Systems-Vol 1.Curran Associates Inc., Lake Tahoe, Nevada2012: 1097-1105
- Comparison of outcomes in DeBakey type AI versus AII aortic dissection.Am J Cardiol. 2018; 122: 689-695
- A machine learning model to classify aortic dissection patients in the early diagnosis phase.Sci Rep. 2019; 9: 2701
- A study of aortic dissection screening method based on multiple machine learning models.J Thorac Dis. 2020; 12: 605-614
- Computed tomography use in the adult emergency department of an academic urban hospital from 2001 to 2007.Ann Emerg Med. 2010; 56: 591-596
- Increasing utilization of computed tomography in the adult emergency department, 2000-2005.Emerg Radiol. 2006; 13: 25-30
- Can we open the black box of AI?.Nature. 2016; 538: 20-23
Yang Z, Yang D, Dyer C, He X, Smola A, Hovy E. Hierarchical attention networks for document classification. Proceedings of the 2016 conference of the North American chapter of the Association for Computational Linguistics: Human Language Technologies: Association for Computational Linguistics. 2016;1480-1489.
- Learning deep features for discriminative localization. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).IEEE, Las Vegas, Nevada, USA2016
See page 167 for disclosure information.