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[Applications of artificial intelligence in radiology].
Johannes Jahn1,2, Jakob Weiß3, Fabian Bamberg3
1Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Deutschland. johannes.jahn@uniklinik-freiburg.de.
Artificial intelligence (AI) is transforming radiology by enhancing efficiency and accuracy across the patient journey. AI applications improve image acquisition, diagnosis, and reporting, promising a significant impact on radiologists' future roles.
Area of Science:
- Radiology
- Medical Imaging
- Artificial Intelligence
Context:
- Artificial intelligence (AI) is increasingly integrated into routine radiological practice.
- The study reviews AI applications across the entire patient journey in radiology.
Purpose:
- To present current advances and applications of AI in radiology.
- To highlight AI's role from scheduling to reporting and diagnosis.
Summary:
- AI enhances image acquisition (CT, MRI), reducing radiation dose and scan times.
- AI tools improve diagnostic accuracy, including fracture and nodule detection.
- Large language models (LLMs) facilitate structured reporting and worklist prioritization.
Impact:
- AI integration promises increased efficiency and diagnostic accuracy in radiology workflows.
- Seamless integration and proven AI system evidence are crucial for adoption.
- AI applications are poised to significantly influence the future role of radiologists.
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