Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception
出版年份 2023 全文链接
标题
Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception
作者
关键词
-
出版物
INVESTIGATIVE RADIOLOGY
Volume -, Issue -, Pages -
出版商
Ovid Technologies (Wolters Kluwer Health)
发表日期
2023-10-17
DOI
10.1097/rli.0000000000001034
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Artificial intelligence in radiology: trainees want more
- (2023) O.-U. Hashmi et al. CLINICAL RADIOLOGY
- Longitudinal Assessment of Multiple Sclerosis Lesion Load With Synthetic Magnetic Resonance Imaging—A Multicenter Validation Study
- (2023) Sarah Schlaeger et al. INVESTIGATIVE RADIOLOGY
- Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance
- (2023) Thomas Dratsch et al. RADIOLOGY
- Current practical experience with artificial intelligence in clinical radiology: a survey of the European Society of Radiology
- (2022) et al. Insights into Imaging
- The Impact of Emerging Technologies on Residency Selection by Medical Students in 2017 and 2021, With a Focus on Diagnostic Radiology
- (2022) Michael K. Atalay et al. ACADEMIC RADIOLOGY
- To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
- (2021) Patrick Omoumi et al. EUROPEAN RADIOLOGY
- Machine Learning–based Differentiation of Benign and Premalignant Colorectal Polyps Detected with CT Colonography in an Asymptomatic Screening Population: A Proof-of-Concept Study
- (2021) Sergio Grosu et al. RADIOLOGY
- A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology
- (2021) Jane Scheetz et al. Scientific Reports
- An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education
- (2021) Merel Huisman et al. EUROPEAN RADIOLOGY
- Artificial intelligence in radiology: 100 commercially available products and their scientific evidence
- (2021) Kicky G. van Leeuwen et al. EUROPEAN RADIOLOGY
- Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study
- (2021) Loïc Duron et al. RADIOLOGY
- Artificial Intelligence in Chest Radiography Reporting Accuracy
- (2021) Jan Rudolph et al. INVESTIGATIVE RADIOLOGY
- Reduction of missed thoracic findings in emergency whole-body computed tomography using artificial intelligence assistance
- (2021) Johannes Rueckel et al. Quantitative Imaging in Medicine and Surgery
- Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI
- (2021) Ramón Alvarado BIOETHICS
- An Artificial Intelligence–Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study
- (2021) Fatemeh Homayounieh et al. JAMA Network Open
- Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence
- (2021) Ali Guermazi et al. RADIOLOGY
- International evaluation of an AI system for breast cancer screening
- (2020) Scott Mayer McKinney et al. NATURE
- Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry
- (2020) Florian Jungmann et al. ACADEMIC RADIOLOGY
- Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs
- (2020) Johannes Rueckel et al. INVESTIGATIVE RADIOLOGY
- Assessment of the Willingness of Radiologists and Radiographers to Accept the Integration of Artificial Intelligence Into Radiology Practice
- (2020) Mohamed M. Abuzaid et al. ACADEMIC RADIOLOGY
- End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
- (2019) Diego Ardila et al. NATURE MEDICINE
- Impact of the rise of artificial intelligence in radiology: What do radiologists think?
- (2019) Q. Waymel et al. Diagnostic and Interventional Imaging
- A survey on the future of radiology among radiologists, medical students and surgeons: Students and surgeons tend to be more skeptical about artificial intelligence and radiologists may fear that other disciplines take over
- (2019) Jasper van Hoek et al. EUROPEAN JOURNAL OF RADIOLOGY
- Use of a Respondent-Generated Personal Code for Matching Anonymous Adolescent Surveys in Longitudinal Studies
- (2017) Lisa Ripper et al. JOURNAL OF ADOLESCENT HEALTH
- Dermatologist-level classification of skin cancer with deep neural networks
- (2017) Andre Esteva et al. NATURE
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
- (2016) Varun Gulshan et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- The Causes of Medical Malpractice Suits against Radiologists in the United States
- (2012) Jeremy S. Whang et al. RADIOLOGY
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