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Updated: Feb 10, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
The Learning-Adapting-Leveling model: from theory to hypothesis of steps for implementation of basic genome-based
Jonathan A Lal1, Anil Vaidya2, Iñaki Gutiérrez-Ibarluzea3
1Institute for Public Health Genomics, Department of Genetics & Cell Biology, School for Oncology & Developmental Biology (GROW), Faculty of Health Medicine & Life Sciences, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands. j.lal@maastrichtuniversity.nl.
Abstract:
We see a backlog in the effective and efficient integration of personalized medicine applications such as genome-based information and technologies into healthcare systems. This article aims to expand on the steps of a published innovative model, which addresses the bottleneck of real-time integration into healthcare. We present a deconstruction of the Learning-Adapting-Leveling model to simplify the steps. We found out that throughout the technology transfer pipeline, contacts, assessments and adaptations/feedback loops are made with health needs assessment, health technology assessment and health impact assessment professionals in the same order by the academic-industrial complex, resulting in early-on involvement of all stakeholders. We conclude that the model steps can be used to resolve the bottleneck of implementation of personalized medicine application into healthcare systems.
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