The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI
Abstract 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 …
radiology forward by enhancing image analysis and interpretation. The introduction of the …
[HTML][HTML] Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources
Rapid technological advances have transformed medical education, particularly in
radiology, which depends on advanced imaging and visual data. Traditional electronic …
radiology, which depends on advanced imaging and visual data. Traditional electronic …
A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reports
Large language models (LLMs) have shown potential in various applications, including
clinical practice. However, their accuracy and utility in providing treatment recommendations …
clinical practice. However, their accuracy and utility in providing treatment recommendations …
Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs
L Wang, X Chen, XW Deng, H Wen, MK You… - npj Digital …, 2024 - nature.com
The use of large language models (LLMs) in clinical medicine is currently thriving. Effectively
transferring LLMs' pertinent theoretical knowledge from computer science to their application …
transferring LLMs' pertinent theoretical knowledge from computer science to their application …
O structured reporting, where art thou?
The opinion paper published in 2014 by Bosmans et al is certainly among the most
memorable manuscripts on the topic of structured reporting [1]. In their manuscript the …
memorable manuscripts on the topic of structured reporting [1]. In their manuscript the …
Fairness in Large Language Models: A Taxonomic Survey
Large Language Models (LLMs) have demonstrated remarkable success across various
domains. However, despite their promising performance in numerous real-world …
domains. However, despite their promising performance in numerous real-world …
ChatGPT's accuracy on magnetic resonance imaging basics: characteristics and limitations depending on the question type
Our study aimed to assess the accuracy and limitations of ChatGPT in the domain of MRI,
focused on evaluating ChatGPT's performance in answering simple knowledge questions …
focused on evaluating ChatGPT's performance in answering simple knowledge questions …
LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction
Electronic health records (EHRs) contain valuable patient data for health-related prediction
tasks, such as disease prediction. Traditional approaches rely on supervised learning …
tasks, such as disease prediction. Traditional approaches rely on supervised learning …
A Radiomic “Warning Sign” of Progression on Brain MRI in Individuals with MS
BACKGROUND AND PURPOSE: MS is a chronic progressive, idiopathic, demyelinating
disorder whose diagnosis is contingent on the interpretation of MR imaging. New MR …
disorder whose diagnosis is contingent on the interpretation of MR imaging. New MR …
Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images
Z Wen, Y Wang, Y Zhong, Y Hu, C Yang… - Frontiers in …, 2024 - frontiersin.org
Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their
diagnosis and treatment. The rapid advancement of artificial intelligence in imaging …
diagnosis and treatment. The rapid advancement of artificial intelligence in imaging …