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...
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...
BACKGROUND: Labeling unstructured radiology reports is crucial for creating structured datasets that facilitate downstream tasks, such as training large-scale medical imaging models. Current approaches typically rely on Bidirectional Encoder Represen...
IEEE journal of translational engineering in health and medicine
40035027
The high volume of emergency room patients often necessitates head CT examinations to rule out ischemic, hemorrhagic, or other organic pathologies. A system that enhances the diagnostic efficacy of head CT imaging in emergency settings through struct...
As artificial intelligence and digital medicine increasingly permeate healthcare systems, robust governance frameworks are essential to ensure ethical, secure, and effective implementation. In this context, medical image retrieval becomes a critical ...
Automated radiology reporting holds immense clinical potential in alleviating the burdensome workload of radiologists and mitigating diagnostic bias. Recently, retrieval-based report generation methods have garnered increasing attention. These method...
BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of med...
IEEE transactions on pattern analysis and machine intelligence
40031357
Given radiology images, automatic radiology report generation aims to produce informative text that reports diseases. It can benefit current clinical practice in diagnostic radiology. Existing methods typically rely on large-scale medical datasets an...
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...