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This framework introduces AAM-V1 to enhance validation and analysis in MRI image processing, suggesting improved reliability.
This work introduces the Adaptive Analytical Model (AAM-V1) — a foundational, domain-agnostic validation framework designed for internal consistency checking, uncertainty esti-mation, and comparative analysis in complex data-processing systems. Version v0.1 formal-izes the core theoretical ontology of AAM as a universal analytical construct independentof any applied domain, defining the principles of reference-based validation and the FormInvariant (F). Version v0.2 presents an applied instantiation in the context of MRI imageanalysis, demonstrating how the foundational theory can be operationalized as an internalvalidation and audit layer within medical imaging pipelines. The framework is designed as anauxiliary reference mechanism; artificial intelligence systems are treated strictly as assistivecomputational tools and are not considered authors or theoretical contributors.
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ANDRII ARTSYBASHEV (2026) studied this question.
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