Harnessing Neuroplasticity in Artificial Intelligence for Advanced Diagnostics and Clinical Intervention

Awarded 2nd Place at the MSBTE State Level Paper Presentation Competition. The convergence of Artificial Intelligence (AI) and neuroscience is initiating a paradigm shift in healthcare engineering. This paper proposes a neuroplasticity-inspired framework utilizing Spiking Neural Networks (SNNs) and Spike-Timing-Dependent Plasticity (STDP) to emulate the brain's ability to reorganize connections dynamically. The study demonstrates a Tri-Memory architecture (Short-Term, Long-Term, and Permanent Memory) to retain core diagnostic knowledge while adapting to novel clinical data, effectively solving the "catastrophic forgetting" problem.