We scan the top radiology sources so you don’t have to.
From AI breakthroughs to imaging trends, we serve up real-time radiology insights.
-
Imaging Utilization Differences After Telemedicine Versus In-Person Visits
The COVID-19 pandemic resulted in a rapid expansion of telemedicine, but little is known about its impact on diagnostic imaging utilization. This study evaluates differences in imaging utilization after telemedicine versus in-person visits at the national level.
-
Integrating LLMs into Radiology Education: An Interpretation-Centric Framework for Enhanced Learning While Supporting Workflow
Radiology education is challenged by increasing clinical workloads, limiting trainee supervision time and hindering real-time feedback. Large language models (LLMs) can enhance radiology education by providing real-time guidance, feedback, and educational resources while supporting efficient clinical workflows. We present an interpretation-centric framework for integrating LLMs into radiology education subdivided into distinct phases spanning pre-dictation preparation, active dictation support, …
-
Artificial Intelligence and its effect on Radiology Residency Education: Current Challenges, Opportunities, and Future Directions
Artificial intelligence has become an impressive force manifesting itself in the radiology field, improving workflows, and influencing clinical decision-making. With this increasing presence, a closer look at how residents can be properly exposed to this technology is needed. Within this paper, we aim to discuss the three pillars central to a trainee’s experience including education on AI, AI-Education tools, and clinical implementation of AI. An already overcrowded clinical residency curricula …
-
Near Peer Mentoring: An Opportunity for Trainees and Departments to Thrive
Given time and resource constraints in academic medical centers, creation of near peer mentoring opportunities has advantages for all individual and department stakeholders. However, many residents may feel unprepared and uncomfortable when asked to participate in these interactions. After reviewing available literature, advantages for incorporation of near peer mentoring and a suggested framework for incorporation of a mentoring curriculum into residency is provided.
-
Remote Arbitrage in Radiology: Multiple Affiliations as a Specialty Specific Adaptation to Changing Practice Demands
To analyze trends from 2017 to 2024 in the number of group and state affiliations among Medicare-serving physicians, with emphasis on diagnostic radiologists.
-
A Hitchhiker's Guide to Good Prompting Practices for Large Language Models in Radiology
Large language models (LLMs) are reshaping radiology through their advanced capabilities in tasks such as medical report generation and clinical decision support. However, their effectiveness is heavily influenced by prompt engineering—the design of input prompts that guide the model’s responses. This review aims to illustrate how different prompt engineering techniques, including zero-shot, one-shot, few-shot, chain of thought, and tree of thought, affect LLM performance in a radiology context.
-
Of Prompt Engineers and Babel Fish
By now, you’ve almost certainly heard of Chat Generative Pre-Trained Transformer (ChatGPT) and more recently, DeepSeek, artificial intelligence (AI) chatbots based on GPT large language models (LLMs) [1,2]. One way that a foundational GPT LLM can be adapted for targeted task-specific or subject matter domain-specific systems is by prompt engineering. Prompt engineering involves creating instructions for the model using natural language text questions or commands that may include relevant context…