Results 11 to 20 of about 12,340,531 (359)
陆军军医大学学报, 2023 As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continued to spread and mutate, our national epidemic prevention and control has entered a new stage since November 2022, and the Diagnosis and Treatment Protocol for SARS-CoV-2 ...
Cardiothoracic Group of Radiology Branch of Chongqing Medical Association, Chongqing Quality Control Center for Medical Imaging
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Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains [PDF]
arXiv.org, 2022 Multi-modal foundation models are typically trained on millions of pairs of natural images and text captions, frequently obtained through web-crawling approaches.
P. Chambon +3 more
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Bioengineering, 2023 The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on ...
Luís Pinto-Coelho
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A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope
Sustainability, 2023 This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and transfer learning in the context of medical imaging. Medical imaging plays a critical role in the diagnosis and treatment of diseases, and CNN-based models have ...
A. Salehi +7 more
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Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging
Diagnostics, 2023 This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making its foray into radiology, a move that is catalysing transformational shifts in the healthcare landscape.
Reabal Najjar
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Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives [PDF]
Medical Image Anal., 2022 Transformer, one of the latest technological advances of deep learning, has gained prevalence in natural language processing or computer vision. Since medical imaging bear some resemblance to computer vision, it is natural to inquire about the status quo
Jun Li +5 more
semanticscholar +1 more source
A Guide to Cross-Validation for Artificial Intelligence in Medical Imaging.
Radiology: Artificial Intelligence, 2023 Artificial intelligence (AI) is being increasingly used to automate and improve technologies within the field of medical imaging. A critical step in the development of an AI algorithm is estimating its prediction error through cross-validation (CV).
T. Bradshaw +3 more
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Robust and Efficient Medical Imaging with Self-Supervision [PDF]
arXiv.org, 2022 Recent progress in Medical Artificial Intelligence (AI) has delivered systems that can reach clinical expert level performance. However, such systems tend to demonstrate sub-optimal"out-of-distribution"performance when evaluated in clinical settings ...
Shekoofeh Azizi +33 more
semanticscholar +1 more source
Applying Deep Learning to Medical Imaging: A Review
Applied Sciences, 2023 Deep learning (DL) has made significant strides in medical imaging. This review article presents an in-depth analysis of DL applications in medical imaging, focusing on the challenges, methods, and future perspectives.
H. Zhang, Yufei Qie
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Medical emergencies in medical imaging [PDF]
BMJ Quality & Safety, 2012 Sending inpatients to the medical imaging department is sometimes tantamount to discharging them from hospital for hours at a time. Consider, for example, a patient with an unexplained acute abdomen where an urgent CT scan is indicated. Patient transport, logistical delays and the procedure itself may lead to gaps in monitoring vital signs, providing ...
Donald A. Redelmeier, John A Staples
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