AIMC Topic: Radiologists
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Establishing robust governance of clinical artificial intelligence software - Why radiologists should lead.
Clinical imaging
Apr 20, 2024
The virtual reference radiologist: comprehensive AI assistance for clinical image reading and interpretation.
European radiology
Apr 16, 2024
OBJECTIVES: Large language models (LLMs) have shown potential in radiology, but their ability to aid radiologists in interpreting imaging studies remains unexplored. We investigated the effects of a state-of-the-art LLM (GPT-4) on the radiologists' d...
AI in radiology: Legal responsibilities and the car paradox.
European journal of radiology
Apr 10, 2024
The integration of AI in radiology raises significant legal questions about responsibility for errors. Radiologists fear AI may introduce new legal challenges, despite its potential to enhance diagnostic accuracy. AI tools, even those approved by reg...
Understanding Bias in Artificial Intelligence: A Practice Perspective.
AJNR. American journal of neuroradiology
Apr 8, 2024
In the fall of 2021, several experts in this space delivered a Webinar hosted by the American Society of Neuroradiology (ASNR) Diversity and Inclusion Committee, focused on expanding the understanding of bias in artificial intelligence, with a health...
Artificial Intelligence and Breast US: Radiologists Won't Regret Opening Pandora's Box.
Academic radiology
Apr 6, 2024
Radiologists and trainees' perspectives on artificial intelligence.
Radiologia
Apr 4, 2024
BACKGROUND AND OBJECTIVES: The purpose of this study was to investigate perspectives held by radiologists on the use of artificial intelligence (AI) in their day-to-day work and to identify factors limiting its routine implementation.
The radiologist as a physician - artificial intelligence as a way to overcome tension between the patient, technology, and referring physicians - a narrative review.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Apr 3, 2024
BACKGROUND: Large volumes of data increasing over time lead to a shortage of radiologists' time. The use of systems based on artificial intelligence (AI) offers opportunities to relieve the burden on radiologists. The AI systems are usually optimized...
The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI.
Japanese journal of radiology
Mar 29, 2024
The advent of Deep Learning (DL) has significantly propelled the field of diagnostic radiology forward by enhancing image analysis and interpretation. The introduction of the Transformer architecture, followed by the development of Large Language Mod...
How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review.
Clinical radiology
Mar 19, 2024
BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy ...
Heterogeneity and predictors of the effects of AI assistance on radiologists.
Nature medicine
Mar 19, 2024
The integration of artificial intelligence (AI) in medical image interpretation requires effective collaboration between clinicians and AI algorithms. Although previous studies demonstrated the potential of AI assistance in improving overall clinicia...
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