Routine Usage of AI-based Chest X-ray Reading Support in a Multi-site Medical Supply Center
Karsten Ridder, Alexander Preuhs, Axel Mertins, Clemens Joerger

TL;DR
This study demonstrates that a commercially available AI system for chest X-ray analysis can be effectively integrated into multi-site clinical workflows, providing continuous support to radiologists and clinicians with robust performance.
Contribution
The paper presents the successful implementation and validation of an AI-based chest X-ray reading support system across multiple clinical sites, highlighting its practicality and benefits.
Findings
AI system supports 24/7 clinical decision-making
Robust performance across different sites and X-ray systems
Improves workflow efficiency and diagnostic confidence
Abstract
Research question: How can we establish an AI support for reading of chest X-rays in clinical routine and which benefits emerge for the clinicians and radiologists. Can it perform 24/7 support for practicing clinicians? 2. Findings: We installed an AI solution for Chest X-ray in a given structure (MVZ Uhlenbrock & Partner, Germany). We could demonstrate the practicability, performance, and benefits in 10 connected clinical sites. 3. Meaning: A commercially available AI solution for the evaluation of Chest X-ray images is able to help radiologists and clinical colleagues 24/7 in a complex environment. The system performs in a robust manner, supporting radiologists and clinical colleagues in their important decisions, in practises and hospitals regardless of the user and X-ray system type producing the image-data.
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging · Digital Radiography and Breast Imaging · Lung Cancer Diagnosis and Treatment
