AIMC Topic: Radiology Information Systems

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The Evolution of Radiology Image Annotation in the Era of Large Language Models.

Radiology. Artificial intelligence
Although there are relatively few diverse, high-quality medical imaging datasets on which to train computer vision artificial intelligence models, even fewer datasets contain expertly classified observations that can be repurposed to train or test su...

Leveraging GPT-4 enables patient comprehension of radiology reports.

European journal of radiology
OBJECTIVE: To assess the feasibility of using GPT-4 to simplify radiology reports into B1-level Dutch for enhanced patient comprehension.

PRECISE framework: Enhanced radiology reporting with GPT for improved readability, reliability, and patient-centered care.

European journal of radiology
BACKGROUND: The PRECISE framework, defined as Patient-Focused Radiology Reports with Enhanced Clarity and Informative Summaries for Effective Communication, leverages GPT-4 to create patient-friendly summaries of radiology reports at a sixth-grade re...

Comparing a Top-Down and a Bottom-Up Approach for Implementing AI in Radiology Practice.

Studies in health technology and informatics
This paper examines how two health regions in Norway adopted different strategies for implementing commercial AI algorithms to outline. One region employs a top-down, research-driven approach, while the other takes a bottom-up, innovation-focused app...

Participatory Co-Creation of an AI-Supported Patient Information System: A Multi-Method Qualitative Study.

Studies in health technology and informatics
In radiology and other medical fields, informed consent often rely on paper-based forms, which can overwhelm patients with complex terminology. These forms are also resource-intensive. The KIPA project addresses these challenges by developing an AI-a...

Open-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters.

Radiology. Artificial intelligence
Purpose To develop and evaluate an automated system for extracting structured clinical information from unstructured radiology and pathology reports using open-weight language models (LMs) and retrieval-augmented generation (RAG) and to assess the ef...

Development and Evaluation of an Automated Protocol Recommendation System for Chest CT Using Natural Language Processing With CLEVER Terminology Word Replacement.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To evaluate the clinical performance of a Protocol Recommendation System (PRS) automatic protocolling of chest CT imaging requests. 322 387 consecutive historical imaging requests for chest CT between 2017 and 2022 were extracted from a radiology i...

Accuracy of Large Language Model-based Automatic Calculation of Ovarian-Adnexal Reporting and Data System MRI Scores from Pelvic MRI Reports.

Radiology
Background Ovarian-Adnexal Reporting and Data System (O-RADS) for MRI helps assign malignancy risk, but radiologist adoption is inconsistent. Automatic assignment of O-RADS scores from reports could increase adoption and accuracy. Purpose To evaluate...

Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models.

Radiology
Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated quality improvement efforts focusing on reproducible assessments of the completeness of free-text clinical histories have relied on tedious manual anal...