AIBullisharXiv – CS AI · 9h ago7/10
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Integrating Mechanistic and Data-Driven Models for Neurological Disorders through Differentiable Programming
Researchers propose hybrid computational models combining mechanistic physics-based solvers with deep learning to improve neurological disorder diagnosis and treatment planning. These integrative approaches—using residual modeling, Neural ODEs, and solver-in-the-loop architectures—overcome limitations of purely mechanistic or data-driven methods alone, demonstrating superior performance in modeling brain tumors, Alzheimer's disease, and stroke progression.