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, …
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.
-
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 …
-
CCTA Study: Plaque Burden Offers No Prognostic Benefit for Predicting Cardiac Events in Patients with Acute Chest Pain
For patients who had coronary CTA for acute chest pain, emerging research found no significant association between plaque burden grades with CAD-RADS 2.0 and cardiac events.
-
More ultrasound cuts risks in pregnancies with less fetal movement
Additional Doppler ultrasound in pregnant women who feel less fetal movement leads to fewer complications compared to usual care…
-
Body Composition Analysis in HF: Time to Replace BMI?
A recent meta-analysis prompts consideration of measurements of visceral and subcutaneous adiposity to better estimate cardiovascular risk than BMI. JACC: Heart Failure
-
Can AI Enhance Ultrasound Detection of Cardiac Amyloidosis? What a Multicenter Study Reveals
EchoGo Amyloidosis, an echocardiography-based AI screening software, demonstrated a 93 percent AUROC for cardiac amyloidosis detection in a new multicenter study.
-
AI Outperforms Humans in Mammography Analysis
An artificial intelligence tool outperforms human readers in diagnostic mammography but shows lower accuracy at the lesion level than at the breast level, a study shows. Medscape News UK
-
Peripheral vision training improves lesion detection
Enhancing students’ peripheral visual perception improved their lesion detection skills.