Neuromorphic and Bio-Inspired Computing for Intelligent Healthcare Networks
Keywords:
Li and Príncipe (2021), Zhou et al. (2021), artificial neural networks (ANNs).Abstract
Spiking Neural Networks and bio-inspired computing systems have come up as viable
technologies that can revolutionize healthcare networks by offering effective, scalable, and
real-time medical data processing solutions. This article discusses the unification of Spiking
Neural Networks and memristor-based learning into healthcare applications, including real
time monitoring of patients, disease prognosis, and tailored treatment protocols. The suggested
techniques provide significant energy efficiency gains, ranging as low as 0.3 milliwatts per
operation while preserving processing rates of 2.0 milliseconds. System performance is
measured on key parameters such as accuracy (up to 93.0%) and system reliability (with 99.2%
uptime). Bio-inspired optimization techniques, such as Particle Swarm Optimization (PSO)
and Genetic Algorithms (GA), are also employed for resource planning and treatment planning
