Domain-Specific AI Application in Medical Imaging: Use Cases

Author	Erik Ranschaert	en
Issued Date	2019-11-30	en
Abstract	Background: In the context of ongoing digitization in healthcare, due to the uprise of machine learning and deep learning, new tools are being developed for implementation in radiology practice. These AI-based applications can be used not only for image analysis in different domains, but also for other parts of the radiological workflow. This will be illustrated with several use cases. Objectives: By listening to this lecture, the audience is expected to: Outline: AI-based applications can be used for many different purposes in radiology. In each clinical practice, it is essential, however, to define the right use cases for implementing such tools. Furthermore, it is crucial to evaluate the accuracy and value of these tools since the real-world data can be different from the data by which the algorithms are trained. In the Netherlands cancer institute, AI tools are being developed and tested, for both improving patient care and optimizing the radiological workflow. A concise overview is given of the potency of these new tools and different challenges that this project is being confronted with.	en
DOI	https://doi.org/10.5812/iranjradiol.99306	en
Publisher	Brieflands	en
Title	Domain-Specific AI Application in Medical Imaging: Use Cases	en
Type	Abstract	en

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