ProjectBenchmarking debiasing methods for artificial intelligence in neuroimaging research

Basic data

Title:
Benchmarking debiasing methods for artificial intelligence in neuroimaging research
Duration:
01/02/2026 to 31/01/2028
Abstract / short description:
This project aims to address the critical issue of bias and fairness in artificial intelligence (AI) applications in neuroimaging, with the goal of promoting fairness and equity in healthcare. The study will systematically benchmark debiasing methods and evaluate them against fairness metrics, which can then be used to develop fairer AI models for clinical use. Furthermore, an open-source toolbox is being developed that will enable researchers and stakeholders to evaluate fairness metrics and apply debiasing methods to various datasets and predictive tasks, particularly in the field of clinical neuroimaging. By reducing algorithmic bias, this project aims to improve the inclusivity and reliability of AI models in clinical neuroimaging.
Keywords:
neuroimaging
bias
fairness

Involved staff

Managers

Faculty of Medicine
University of Tübingen

Local organizational units

Hertie Institute for Artificial Intelligence in Brain Health (HIAI)
Non-clinical institutes
Faculty of Medicine

Funders

Bonn, Nordrhein-Westfalen, Germany
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