KI - Künstliche Intelligenz - CfP Special Issue: AI in Healthcare and the Public Sector

Scope: Healthcare and the public sector are fields that provide many interesting challenges as an application area for AI technologies: there is a plethora of data in some cases and only a handful of data points in others. Data is noisy, influences are uncertain, and causal interactions at times not fully understood. The scenarios under investigation can become very large with multiple players with diverse interests coming together. Researchers therefore deal with a rich set of different problems. Consequently solutions are based on a wide array of techniques. In addition, human-centered and explainable AI are of particular importance when providing automated data analysis services or decision support. Ethical and privacy considerations also play a large role in healthcare applications and applications in the public sector as they possibly deal with very personal information. For enabling AI to provide a rich set of helpful services, advances are necessary that not only improve technologies but also consider ethical, legal, and social implications and increase acceptance in society at large.

This special issue aims at providing an overview of work in AI in healthcare and the public sector regarding, but not limited to, the following topics:

• Data analysis techniques including dealing with heterogeneous data sources or data streams
• Decision support
• Robotics in healthcare
• Human-centered AI, human-computer interaction
• Trustworthy AI, explainability, transparency
• Ethical, legal and social implications of AI

The special issue welcomes technical contributions (of up to 20 pages), abstracts (4 pages), e.g., on doctoral theses or habilitations, system descriptions (4 pages), project reports (4 pages), or discussion articles (4-8 pages). 

All submissions will be peer-reviewed. 

Submission deadline for articles: 15 June 2023

Contact:

Tanya Braun (University of Münster), tanya (this opens in a new tab). (this opens in a new tab)braun (this opens in a new tab)@ (this opens in a new tab)uni (this opens in a new tab)- (this opens in a new tab)muenster (this opens in a new tab). (this opens in a new tab)de (this opens in a new tab)

Christian Igel (University of Copenhagen, Denmark), igel@di.ku.dk

Ralf Möller (University of Lübeck, DFKI), moeller (this opens in a new tab)@ (this opens in a new tab)uni (this opens in a new tab)- (this opens in a new tab)luebeck (this opens in a new tab). (this opens in a new tab)de (this opens in a new tab) 

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