AI Medical Compendium Journal:
AJR. American journal of roentgenology

Showing 1 to 10 of 169 articles

Prompt Engineering for Large Language Models in Interventional Radiology.

AJR. American journal of roentgenology
Prompt engineering plays a crucial role in optimizing artificial intelligence (AI) and large language model (LLM) outputs by refining input structure, a key factor in medical applications where precision and reliability are paramount. This Clinical P...

Multimodal Large Language Model With Knowledge Retrieval Using Flowchart Embedding for Forming Follow-Up Recommendations for Pancreatic Cystic Lesions.

AJR. American journal of roentgenology
The American College of Radiology (ACR) Incidental Findings Committee (IFC) algorithm provides guidance for pancreatic cystic lesions (PCL) management. Its implementation using plain-text large language model (LLM) solutions is challenging given tha...

Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study.

AJR. American journal of roentgenology
Radiologists are prone to missing some colorectal cancers (CRCs) on routine abdominopelvic CT examinations that are in fact detectable on the images. The purpose of this study was to develop an artificial intelligence (AI) model to detect CRC on ro...

Use of ChatGPT Large Language Models to Extract Details of Recommendations for Additional Imaging From Free-Text Impressions of Radiology Reports.

AJR. American journal of roentgenology
Automated extraction of actionable details of recommendations for additional imaging (RAIs) from radiology reports could facilitate tracking and timely completion of clinically necessary RAIs and thereby potentially reduce diagnostic delays. The pu...

CT-Based Body Composition Measures and Systemic Disease: A Population-Level Analysis Using Artificial Intelligence Tools in Over 100,000 Patients.

AJR. American journal of roentgenology
CT-based abdominal body composition measures have shown associations with important health outcomes. Advances in artificial intelligence (AI) now allow deployment of tools that measure body composition in large patient populations. The purpose of t...

Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.

AJR. American journal of roentgenology
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...

Deployment of Artificial Intelligence in Radiology: Strategies for Success.

AJR. American journal of roentgenology
Radiology, as a highly technical and information-rich medical specialty, is well suited for artificial intelligence (AI) product development, and many U.S. FDA-cleared AI medical devices are authorized for uses within the specialty. In this Clinical ...

Multiparametric MRI Radiomics With Machine Learning for Differentiating HER2-Zero, -Low, and -Positive Breast Cancer: Model Development, Testing, and Interpretability Analysis.

AJR. American journal of roentgenology
MRI radiomics has been explored for three-tiered classification of HER2 expression levels (i.e., HER2-zero, HER2-low, or HER2-positive) in patients with breast cancer, although an understanding of how such models reach their predictions is lacking. ...

Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

AJR. American journal of roentgenology
Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligenc...

ChatGPT and Large Language Models in Radiology: Perspectives From the Field.

AJR. American journal of roentgenology
Generative artificial intelligence (AI) and large language models (LLMs) are increasingly being recognized as tools with the potential to transform many industries, including health care. Implementation and use of these tools among radiologists is li...