Special Issue: Present and Future Perspectives of Vascular Interventional Radiology

Frandon, Julien; Beregi, Jean‐Paul

doi:10.3390/jpm13071131

Cited by 1 publication

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The discipline of vascular and interventional radiology (VIR) has also seen significant advancements in recent years, with an increase in the number of procedures performed, subspecialization, and improved accuracy in interventions. 3 The demonstrated AI applications in various VIR use cases abounds including AI-assisted endovascular clot retrieval for acute ischemic stroke, predicting responses to transcatheter arterial chemoembolization in hepatocellular carcinoma, AI-guided ultrasound in echocardiography, and angiography-based ML algorithms for real-time estimation of fractional flow reserve. 4 5 So, as VIR techniques and procedures mature and achieve wider acceptance, it could prove more useful in multidisciplinary care with the incorporation of AI potentially leading to improved outcomes for all stakeholders.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Potentials of Large Language Models in Vascular and Interventional Radiology: Opportunities and Challenges

Togunwa,

Ajibade,

Uche-Orji

et al. 2024

The Arab Journal of Interventional Radiology

View full text Add to dashboard Cite

The increasing integration of artificial intelligence (AI) in healthcare, particularly in vascular and interventional radiology (VIR), has opened avenues for enhanced efficiency and precision. This narrative review delves into the potential applications of large language models (LLMs) in VIR, with a focus on Chat Generative Pre-Trained Transformer (ChatGPT) and similar models. LLMs, designed for natural language processing, exhibit promising capabilities in clinical decision-making, workflow optimization, education, and patient-centered care. The discussion highlights LLMs' ability to analyze extensive medical literature, aiding radiologists in making informed decisions. Moreover, their role in improving clinical workflow, automating report generation, and intelligent patient scheduling is explored. This article also examines LLMs' impact on VIR education, presenting them as valuable tools for trainees. Additionally, the integration of LLMs into patient education processes is examined, highlighting their potential to enhance patient-centered care through simplified and accurate medical information dissemination. Despite these potentials, this paper discusses challenges and ethical considerations, including AI over-reliance, potential misinformation, and biases. The scarcity of comprehensive VIR datasets and the need for ongoing monitoring and interdisciplinary collaboration are also emphasized. Advocating for a balanced approach, the combination of LLMs with computer vision AI models addresses the inherently visual nature of VIR. Overall, while the widespread implementation of LLMs in VIR may be premature, their potential to improve various aspects of the discipline is undeniable. Recognizing challenges and ethical considerations, fostering collaboration, and adhering to ethical standards are essential for unlocking the full potential of LLMs in VIR, ushering in a new era of healthcare delivery and innovation.

show abstract

Section: Introductionmentioning

confidence: 99%

Exploring the Potentials of Large Language Models in Vascular and Interventional Radiology: Opportunities and Challenges

Togunwa,

Ajibade,

Uche-Orji

et al. 2024

The Arab Journal of Interventional Radiology

View full text Add to dashboard Cite

show abstract

Special Issue: Present and Future Perspectives of Vascular Interventional Radiology

Abstract: The field of vascular interventional radiology has witnessed remarkable advancements, transforming the landscape of patient care for both vascular and non-vascular pathologies [...]

Cited by 1 publication

References 16 publications

Exploring the Potentials of Large Language Models in Vascular and Interventional Radiology: Opportunities and Challenges

Exploring the Potentials of Large Language Models in Vascular and Interventional Radiology: Opportunities and Challenges

Contact Info

Product

Resources

About