Special Focus Session
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SF 20-1
5 min
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Chairperson's introduction
Laure S. Fournier, Paris / France
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SF 20-2
18 min
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Open-source tools for the non-expert radiologist
Guillaume Chassagnon, Paris / France
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1. To define languages, softwares, and libraries.
2. To explain how to start programming and which educational resources are best adapted to radiologists. 3. To review simple projects with which to start artificial intelligence research. |
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SF 20-3
18 min
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Data preparation for artificial intelligence: a step-by-step approach
Martin J. Willemink, Stanford, CA / United States
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1. To explain how data should be prepared for the development of artificial intelligence tools.
2. To define which steps are necessary to be compliant with regulatory principles. 3. To illustrate which new approaches may help data availability for artificial intelligence research. |
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SF 20-4
18 min
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Developing methodology for quality assurance in machine learning
Lena Maier-Hein, Heidelberg / Germany
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1. To explain which issues may impact the quality of output of machine learning-based tools.
2. To define strategies to control results of machine learning algorithms. 3. To illustrate which new approaches may be used for quality assurance in machine learning-based imaging tools. |
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SF 20-5
18 min
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What do the neighbours do and how can we collaborate: machine learning in pathology
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1. To illustrate the clinical applications of artificial intelligence tools in pathology.
2. To define low-hanging fruits versus major pitfalls for artificial intelligence in pathology. 3. To demonstrate common fields of research between pathology and radiology. |
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SF 20-6
13 min
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Panel discussion: From hype to practical: what's next for artificial intelligence?
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