AIMC Topic: Radiology Information Systems

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Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports.

European radiology
OBJECTIVE: Radiology reporting is an essential component of clinical diagnosis and decision-making. With the advent of advanced artificial intelligence (AI) models like GPT-4 (Generative Pre-trained Transformer 4), there is growing interest in evalua...

DICOM Image ANalysis and Archive (DIANA): an Open-Source System for Clinical AI Applications.

Journal of digital imaging
In the era of data-driven medicine, rapid access and accurate interpretation of medical images are becoming increasingly important. The DICOM Image ANalysis and Archive (DIANA) system is an open-source, lightweight, and scalable Python interface that...

A deep look into radiomics.

La Radiologia medica
Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into ...

Extracting clinical terms from radiology reports with deep learning.

Journal of biomedical informatics
Extracting clinical terms from free-text format radiology reports is a first important step toward their secondary use. However, there is no general consensus on the kind of terms to be extracted. In this paper, we propose an information model compri...

RadLex Normalization in Radiology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Radiology reports have been widely used for extraction of various clinically significant information about patients' imaging studies. However, limited research has focused on standardizing the entities to a common radiology-specific vocabulary. Furth...

Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.

Journal of digital imaging
The ideal radiology report reduces diagnostic uncertainty, while avoiding ambiguity whenever possible. The purpose of this study was to characterize the use of uncertainty terms in radiology reports at a single institution and compare the use of thes...

Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.

European journal of radiology
PURPOSE: Aim of this study was to develop and evaluate a software toolkit, which allows for a fully automated body composition analysis in contrast enhanced abdominal computed tomography leveraging the strengths of both, quantitative information from...

From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.

Seminars in musculoskeletal radiology
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...

The Importance of Imaging Informatics and Informaticists in the Implementation of AI.

Academic radiology
Imaging informatics is critical to the success of AI implementation in radiology. An imaging informaticist is a unique individual who sits at the intersection of clinical radiology, data science, and information technology. With the ability to unders...

Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

Journal of the American College of Radiology : JACR
OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance in...