Trustworthy AI in MICCAI
MICCAI Tutorial
September 22 2022, Singapore
FUTURE-AI: International guidelines and consensus recommendations for trustworthy AI
Dr. Karim Lekadir
Director, Artificial Intelligence in Medicine Lab
University of Barcelona
Abstract:
Despite major advances in AI for medical imaging, the deployment and deployment of AI technologies remain limited compared to the research output in the field. Over the recent years, concerns have been expressed on the potential risks,
ethical implications and general lack of trust associated with emerging AI technologies in the real world. In particular, AI tools continue to be viewed as complex and opaque, prone to errors and biases, and potentially unsafe or unethical
for patients. This talk will present FUTURE-AI (www.future-ai.eu), a code of practice recently defined by an international consortium of over 80 experts in the field, to ensure future medical AI tools are developed to be trusted and accepted
by patients, health professionals, health organisations and authorities. In particular, the guidelines recommend building AI solutions that are Fair, Universal, Traceable, Usable, Robust and Explainable (FUTURE-AI) and offer concrete recommendations
that cover the whole AI production lifecycle, from AI design and development to AI validation and operation. A concrete example will be presented in the field of treatment planning in breast cancer to illustrate the potential of the FUTURE-AI
guidelines.
Bio:
Karim Lekadir is the Director of the Artificial Intelligence in Medicine Lab at the University of Barcelona (BCN-AIM). His current research focuses on the development of new medical AI tools from complex biomedical data,
such as imaging, biological, clinical and environmental data. He is particularly interested in trustworthy AI and related methods such as domain adaptation, bias correction, uncertainty estimation and AI validation. He is currently
the Scientific Coordinator of three European projects (euCanSHare, EuCanImage, EarlyCause) in the field of medical AI.
He is the recipient of a research grant from the European Research Council (ERC) to develop novel AI methods for accessible medical imaging in low-to-middle income countries.
