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Mashup Score: 2Radiology: Artificial Intelligence - 2 day(s) ago
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username? by Tugba Akinci D’Antonoli, MD and Merel Huisman, MD, PhD The May 2024 edition of the journal’s “#RadAIchat” tweet chat, titled “Medical AI Regulations: A Primer & Future Directions,” featured an expert panel: The chat aimed to untangle the complexities of medical AI regulations. As AI systems become increasingly integrated
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 1
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username? It seems obvious now, but I can still recall my fascination when I first learned about the Maisonneuve fracture. Every radiologist is taught when you see a fracture of the medial malleolus with a widening of the distal tibiofibular syndesmosis on ankle radiographs to look higher for the proximal fibular fracture that may
Source: pubs.rsna.orgCategories: General Medicine News, Hem/OncsTweet
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Mashup Score: 3Precision and Test-Retest Repeatability of Stiffness Measurement with MR Elastography: A Multicenter Phantom Study - 8 day(s) ago
Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms. Materials and Methods In this study, three cylindrical phantoms made of polyvinyl chloride gel mimicking different degrees of liver stiffness in humans (phantoms 1–3: soft, medium, and hard stiffness, respectively) were evaluated. Between January 2021 and January 2022, phantoms were circulated between five different centers and scanned with 10 MRE-equipped clinical 1.5-T and 3-T systems from three major vendors, using two-dimensional (2D) gradient-recalled echo (GRE) imaging and/or 2D spin-echo (SE) echo-planar imaging (EPI). Similar MRE acquisition parameters, hardware, and
Source: pubs.rsna.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 3Efficient Health Care: Decreasing MRI Scan Time - 13 day(s) ago
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username?
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 3Efficient Health Care: Decreasing MRI Scan Time - 21 day(s) ago
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username?
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 4MRI in the Evaluation of Cryptogenic Stroke and Embolic Stroke of Undetermined Source - 29 day(s) ago
Cryptogenic stroke refers to a stroke of undetermined etiology. It accounts for approximately one-fifth of ischemic strokes and has a higher prevalence in younger patients. Embolic stroke of undetermined source (ESUS) refers to a subgroup of patients with nonlacunar cryptogenic strokes in whom embolism is the suspected stroke mechanism. Under the classifications of cryptogenic stroke or ESUS, there is wide heterogeneity in possible stroke mechanisms. In the absence of a confirmed stroke etiology, there is no established treatment for secondary prevention of stroke in patients experiencing cryptogenic stroke or ESUS, despite several clinical trials, leaving physicians with a clinical dilemma. Both conventional and advanced MRI techniques are available in clinical practice to identify differentiating features and stroke patterns and to determine or infer the underlying etiologic cause, such as atherosclerotic plaques and cardiogenic or paradoxical embolism due to occult pelvic venous thr
Source: pubs.rsna.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 9Energy and Greenhouse Gas Emission Savings Associated with Implementation of an Abbreviated Cardiac MRI Protocol - 1 month(s) ago
Supplemental material is available for this article. See also the article by Lenkinski and Rofsky in this issue. See also the article by McKee et al in this issue.
Source: pubs.rsna.orgCategories: General Medicine News, Cardiologists1Tweet
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Mashup Score: 3
Climate change adversely affects the well-being of humans and the entire planet. A planetary health framework recognizes that sustaining a healthy planet is essential to achieving individual, community, and global health. Radiology contributes to the climate crisis by generating greenhouse gas (GHG) emissions during the production and use of medical imaging equipment and supplies. To promote planetary health, strategies that mitigate and adapt to climate change in radiology are needed. Mitigation strategies to reduce GHG emissions include switching to renewable energy sources, refurbishing rather than replacing imaging scanners, and powering down unused scanners. Radiology departments must also build resiliency to the now unavoidable impacts of the climate crisis. Adaptation strategies include education, upgrading building infrastructure, and developing departmental sustainability dashboards to track progress in achieving sustainability goals. Shifting practices to catalyze these neces
Source: pubs.rsna.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 107Potential of GPT-4 for Detecting Errors in Radiology Reports: Implications for Reporting Accuracy - 1 month(s) ago
Background Errors in radiology reports may occur because of resident-to-attending discrepancies, speech recognition inaccuracies, and large workload. Large language models, such as GPT-4 (ChatGPT; OpenAI), may assist in generating reports. Purpose To assess effectiveness of GPT-4 in identifying common errors in radiology reports, focusing on performance, time, and cost-efficiency. Materials and Methods In this retrospective study, 200 radiology reports (radiography and cross-sectional imaging [CT and MRI]) were compiled between June 2023 and December 2023 at one institution. There were 150 errors from five common error categories (omission, insertion, spelling, side confusion, and other) intentionally inserted into 100 of the reports and used as the reference standard. Six radiologists (two senior radiologists, two attending physicians, and two residents) and GPT-4 were tasked with detecting these errors. Overall error detection performance, error detection in the five error categories
Source: pubs.rsna.orgCategories: General Medicine News, Expert PicksTweet
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Mashup Score: 1Radiology: Artificial Intelligence - 2 month(s) ago
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username? An end-to-end deep learning pipeline provides standardized segmentation for patients with single ventricle physiology (Yao and St. Clair et al). A CNN trained on data from three brain cancer datasets accurately classifies MR image sequences (Mahmutoglu et al). See the latest information about Radiology: Artificial Intelligen
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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