Results 1 to 10 of about 1,293,588 (309)
Convolutional neural networks: an overview and application in radiology
Insights Into Imaging, 2018 Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology.
Rikiya Yamashita
exaly +2 more sources
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
exaly +2 more sources
European Radiology, 2021 Map the current landscape of commercially available artificial intelligence (AI) software for radiology and review the availability of their scientific evidence. We created an online overview of CE-marked AI software products for clinical radiology based
Kicky G Van Leeuwen +2 more
exaly +2 more sources
On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities
Radiology: Artificial Intelligence, 2020 As artificial intelligence (AI) systems begin to make their way into clinical radiology practice, it is crucial to assure that they function correctly and that they gain the trust of experts.
Mauricio Reyes +2 more
exaly +2 more sources
European Radiology, 2020 This document from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI) aims to present the main imaging features, and the role of CT scan in the early diagnosis of COVID-19, describing, in particular, the typical ...
Marie-pierre Revel +2 more
exaly +2 more sources
Artificial intelligence in radiology
Nature Reviews Cancer, 2018 Ahmed Hosny +2 more
exaly +2 more sources
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
Nature Reviews Clinical Oncology, 2021 Kaustav Bera +2 more
exaly +2 more sources
Towards Generalist Foundation Model for Radiology [PDF]
arXiv.org, 2023 In this study, we aim to initiate the development of Radiology Foundation Model, termed as RadFM. We consider the construction of foundational models from three perspectives, namely, dataset construction, model design, and thorough evaluation.
Chaoyi Wu +4 more
semanticscholar +1 more source
Cross-modal Memory Networks for Radiology Report Generation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments.
Zhihong Chen +3 more
semanticscholar +1 more source
R2GenGPT: Radiology Report Generation with Frozen LLMs [PDF]
Meta-Radiology, 2023 Large Language Models (LLMs) have consistently showcased remarkable generalization capabilities when applied to various language tasks. Nonetheless, harnessing the full potential of LLMs for Radiology Report Generation (R2Gen) still presents a challenge,
Zhanyu Wang +3 more
semanticscholar +1 more source