On July 17, 2024, CWI researchers (E.M.C. Sijben, J.C. Jansen, P.A.N. Bosman, T. Alderliesten) presented their work, "Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals," at GECCO 2024. The study used genetic programming to model tumor growth patterns, focusing on explainability in AI-driven medical research.
This approach aligns with projects like TRUST AI by prioritizing transparency in AI systems. By uncovering general growth patterns and tumor-specific parameters, it provides actionable insights for clinicians, reinforcing the role of explainable AI in high-stakes medical applications.
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