Download Full Text (267 KB)


Technological University Dublin


The European Commission defines that Trustworthy AI should be lawful, ethical and robust. The ethical component and its technical methods are the main focus of the research. According to this, the initial research goal is to create a methodology for evaluating datasets for ML modeling using ethical principles in the healthcare domain. Ethical risk assessment will help to ensure compliance with principles such as privacy, fairness, safety and transparency which are especially important for the Health Care sector. At the same time, risks must be evaluated with respect to AI model performance and possible scenarios of risk mitigation. Ethical risk mitigation techniques involve data modification, elimination of private information from datasets that directly influence AI modelling. Therefore ethical risk mitigation techniques should be carefully selected depending on domain and context. In this research work, we present an analysis of these techniques.

Publication Date



AI, ethical risk assessment, health sector


Computer Sciences


Dr. Fernando Perez Tellez; Dr. Davide Buscaldi


First Annual Teaching and Research Showcase 2023


Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Framework for Trustworthy AI in the Health Sector



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.